Journal articles: '080704 Information Retrieval and Web Search'

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P, Dr Natarajan, and Sonali Pandey. "INFORMATION RETRIEVAL AND WEB SEARCH." International Research Journal of Computer Science 8, no. 8 (August 30, 2021): 215–20. http://dx.doi.org/10.26562/irjcs.2021.v0808.010.

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This article discusses Web search engines; mainly the challenges in indexing the World Wide Web, the user behaviour, and the ranking factors used by these engines. Ranking factors are divided into query-dependent and query-independent factors, the latter of which have become more and more important within recent years. The possibilities of these factors are limited, mainly of those that are based on the widely used link popularity measures. The article concludes with an overview of factors that should be considered to determine the quality of Web search engines.

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Pruski, Cédric, Nicolas Guelfi, and Chantal Reynaud. "Adaptive Ontology-Based Web Information Retrieval." International Journal of Web Portals 3, no. 3 (July 2011): 41–58. http://dx.doi.org/10.4018/ijwp.2011070104.

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Finding relevant information on the Web is difficult for most users. Although Web search applications are improving, they must be more “intelligent” to adapt to the search domains targeted by queries, the evolution of these domains, and users’ characteristics. In this paper, the authors present the TARGET framework for Web Information Retrieval. The proposed approach relies on the use of ontologies of a particular nature, called adaptive ontologies, for representing both the search domain and a user’s profile. Unlike existing approaches on ontologies, the authors make adaptive ontologies adapt semi-automatically to the evolution of the modeled domain. The ontologies and their properties are exploited for domain specific Web search purposes. The authors propose graph-based data structures for enriching Web data in semantics, as well as define an automatic query expansion technique to adapt a query to users’ real needs. The enriched query is evaluated on the previously defined graph-based data structures representing a set of Web pages returned by a usual search engine in order to extract the most relevant information according to user needs. The overall TARGET framework is formalized using first-order logic and fully tool supported.

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Lewandowski, Dirk. "Web searching, search engines and Information Retrieval." Information Services & Use 25, no. 3-4 (January 25, 2006): 137–47. http://dx.doi.org/10.3233/isu-2005-253-402.

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Norouzi, Yaghoub, and Hoda Homavandi. "Image search and retrieval problems in web search engines." Online Information Review 42, no. 6 (October 8, 2018): 752–67. http://dx.doi.org/10.1108/oir-01-2017-0007.

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PurposeThe purpose of this paper is to investigate image search and retrieval problems in selected search engines in relation to Persian writing style challenges.Design/methodology/approachThis study is an applied one, and to answer the questions the authors used an evaluative research method. The aim of the research is to explore the morphological and semantic problems of Persian language in connection with image search and retrieval among the three major and widespread search engines: Google, Yahoo and Bing. In order to collect the data, a checklist designed by the researcher was used and then the data were analyzed by descriptive and inferential statistics.FindingsThe results indicate that Google, Yahoo and Bing search engines do not pay enough attention to morphological and semantic features of Persian language in image search and retrieval. This research reveals that six groups of Persian language features include derived words, derived/compound words, Persian and Arabic Plural words, use of dotted T and the use of spoken language and polysemy, which are the major problems in this area. In addition, the results suggest that Google is the best search engine of all in terms of compatibility with Persian language features.Originality/valueThis study investigated some new aspects of the above-mentioned subject through combining morphological and semantic aspects of Persian language with image search and retrieval. Therefore, this study is an interdisciplinary research, the results of which would help both to offer some solutions and to carry out similar research on this subject area. This study will also fill a gap in research studies conducted so far in this area in Farsi language, especially in image search and retrieval. Moreover, findings of this study can help to bridge the gap between the user’s questions and search engines (systems) retrievals. In addition, the methodology of this paper provides a framework for further research on image search and retrieval in databases and search engines.

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Frikh, Bouchra, and Brahim Ouhbi. "Web Algorithms for Information Retrieval." International Journal of Mobile Computing and Multimedia Communications 6, no. 1 (January 2014): 1–16. http://dx.doi.org/10.4018/ijmcmc.2014010101.

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The World Wide Web has emerged to become the biggest and most popular way of communication and information dissemination. Every day, the Web is expending and people generally rely on search engine to explore the web. Because of its rapid and chaotic growth, the resulting network of information lacks of organization and structure. It is a challenge for service provider to provide proper, relevant and quality information to the internet users by using the web page contents and hyperlinks between web pages. This paper deals with analysis and comparison of web pages ranking algorithms based on various parameters to find out their advantages and limitations for ranking web pages and to give the further scope of research in web pages ranking algorithms. Six important algorithms: the Page Rank, Query Dependent-PageRank, HITS, SALSA, Simultaneous Terms Query Dependent-PageRank (SQD-PageRank) and Onto-SQD-PageRank are presented and their performances are discussed.

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Zhi, Shanshan, and Huanhuan Wang. "A search ranking algorithm for web information retrieval." International Journal of Communication Networks and Distributed Systems 1, no. 1 (2023): 1. http://dx.doi.org/10.1504/ijcnds.2023.10045845.

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Falk, Howard. "World Wide Web search and retrieval." Electronic Library 15, no. 1 (January 1997): 49–55. http://dx.doi.org/10.1108/eb045534.

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Sroka, Marek. "Web Search Engines for Polish Information Retrieval: Questions of Search Capabilities and Retrieval Performance." International Information & Library Review 32, no. 2 (June 2000): 87–98. http://dx.doi.org/10.1080/10572317.2000.10762506.

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Samar, Thaer, Myriam C. Traub, Jacco van Ossenbruggen, Lynda Hardman, and Arjen P. de Vries. "Quantifying retrieval bias in Web archive search." International Journal on Digital Libraries 19, no. 1 (April 18, 2017): 57–75. http://dx.doi.org/10.1007/s00799-017-0215-9.

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Subhashini, R., and V. Jawahar Senthil Kumar. "A Roadmap to Integrate Document Clustering in Information Retrieval." International Journal of Information Retrieval Research 1, no. 1 (January 2011): 31–44. http://dx.doi.org/10.4018/ijirr.2011010103.

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The World Wide Web is a large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Information Retrieval (IR) plays an important role in search engines. Today’s most advanced engines use the keyword-based (“bag of words”) paradigm, which has inherent disadvantages. Organizing web search results into clusters facilitates the user’s quick browsing of search results. Traditional clustering techniques are inadequate because they do not generate clusters with highly readable names. This paper proposes an approach for web search results in clustering based on a phrase based clustering algorithm. It is an alternative to a single ordered result of search engines. This approach presents a list of clusters to the user. Experimental results verify the method s feasibility and effectiveness.

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Chevalier, Max, Christine Julien, and Chantal Soulé-Dupuy. "User Models for Adaptive Information Retrieval on the Web." International Journal of Adaptive, Resilient and Autonomic Systems 3, no. 3 (July 2012): 1–19. http://dx.doi.org/10.4018/jaras.2012070101.

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Searching information can be realized thanks to specific tools called Information Retrieval Systems IRS (also called “search engines”). To provide more accurate results to users, most of such systems offer personalization features. To do this, each system models a user in order to adapt search results that will be displayed. In a multi-application context (e.g., when using several search engines for a unique query), personalization techniques can be considered as limited because the user model (also called profile) is incomplete since it does not exploit actions/queries coming from other search engines. So, sharing user models between several search engines is a challenge in order to provide more efficient personalization techniques. A semantic architecture for user profile interoperability is proposed to reach this goal. This architecture is also important because it can be used in many other contexts to share various resources models, for instance a document model, between applications. It is also ensuring the possibility for every system to keep its own representation of each resource while providing a solution to easily share it.

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Lu, Zhongyu, and Umair Rahman. "Semantic search technology for information retrieval on the web." International Journal of Agent-Oriented Software Engineering 1, no. 2 (2007): 225. http://dx.doi.org/10.1504/ijaose.2007.014408.

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Baeza-Yates, Ricardo. "Information retrieval in the Web: beyond current search engines." International Journal of Approximate Reasoning 34, no. 2-3 (November 2003): 97–104. http://dx.doi.org/10.1016/j.ijar.2003.07.002.

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Veeramalai, Sankaradass, and Arputharaj Kannan. "Intelligent Information Retrieval Using Fuzzy Association Rule Classifier." International Journal of Intelligent Information Technologies 7, no. 3 (July 2011): 14–27. http://dx.doi.org/10.4018/jiit.2011070102.

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As the use of web applications increases, when users use search engines for finding some information by inputting keywords, the number of web pages that match the information increases at a tremendous rate. It is not easy for a user to retrieve the exact web page which contains information he or she requires. In this paper, an approach to web page retrieval system using the hybrid combination of context based and collaborative filtering method employing the concept of fuzzy association rule classification is introduced and the authors propose an innovative clustering of user profiles in order to reduce the filtering space and achieves sub-linear filtering time. This approach can produce recommended web page links for users based on the information that associates strongly with users’ queries quickly with better efficiency and therefore improve the recall, precision of a search engine.

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RAKHSHAN, ARASH, LAWRENCE B. HOLDER, and DIANE J. COOK. "STRUCTURAL WEB SEARCH ENGINE." International Journal on Artificial Intelligence Tools 13, no. 01 (March 2004): 27–44. http://dx.doi.org/10.1142/s0218213004001405.

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We present a new approach in web search engines. The web creates new challenges for information retrieval. The vast improvement in information access is not the only advantage resulting from the keyword search. Additionally, much potential exists for analyzing interests and relationships within the structure of the web. The creation of a hyperlink by the author of a web page explicitly represents a relationship between the source and destination pages which demonstrates the hyperlink structure between web pages. Our web search engine searches not only for the keywords in the web pages, but also for the hyperlink structure between them. Comparing the results of structural web search versus keyword-based search indicates an improved ability to access desired information. We also discuss steps toward mining the queries input to the structural web search engine.

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WANG, SHU, and PHILLIP C. Y. SHEU. "APPLYING SYNTACTICAL INFORMATION IN WEB SEARCH." International Journal of Semantic Computing 04, no. 04 (December 2010): 535–58. http://dx.doi.org/10.1142/s1793351x10001127.

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Web search could be much facilitated if we can better relate the user intention with the meaning of the web content. In this paper, we first survey the various existing methods, focusing on the dilemma that obtaining high accuracy results usually sacrifices the response time. We then propose a novel information retrieval framework to combine keyword-based search and search based on syntactical information. In particular, we design a sequential structure called LSC (Language Sequential Component) to encode syntactical information. Given a sentence, LSC provides a bridge from its syntactical representation and semantic meaning. We also propose a learning algorithm to obtain the LSCs from a training set, a classification algorithm to find the relevant LSCs from a user query to interpret the intentions of the user, and a search framework (called Semantic Search Engine) to incorporate syntactical information into a keyword based search system. Our experiments show the Semantic Search Engine outperforms the keyword-based approach significantly.

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Grishanova, I. J. "Analytical review on information retrieval methods and applications in the Semantic Web." PROBLEMS IN PROGRAMMING, no. 1 (January 2016): 051–72. http://dx.doi.org/10.15407/pp2016.01.051.

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The article describes and analyzes the Information Retrieval (IR) methods and applications in the environment of Semantic Web. The author provided the basic Information Retrieval concepts, problems, models and classification of IR systems on various grounds. Examples of existing modern search engines, as well as highlighted the stages of development and listed a list of functional and architectural features of 3-rd search engines generation. The proposed model of IR extends the classification of search engines and search model with the possibility of finding new objects that have become available in the web, and use knowledge represented in the Semantic Web.

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Alloui, Tarek, Imane Boussebough, and Allaoua Chaoui. "A Particle Swarm Optimization Algorithm for Web Information Retrieval." International Journal of Intelligent Information Technologies 11, no. 3 (July 2015): 15–29. http://dx.doi.org/10.4018/ijiit.2015070102.

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The Web has become the largest source of information worldwide and the information, in its various forms, is growing exponentially. So obtaining relevant and up-to-date information has become hard and tedious. This situation led to the emergence of search engines which index today billions of pages. However, they are generic services and they try to aim the largest number of users without considering their information needs in the search process. Moreover, users use generally few words to formulate their queries giving incomplete specifications of their information needs. So dealing this problem within Web context using traditional approaches is vain. This paper presents a novel particle swarm optimization approach for Web information retrieval. It uses relevance feedback to reformulate user query and thus improve the number of relevant results. In the authors' experimental results, they obtained a significant improvement of relevant results using their proposed approach comparing to what is obtained using only the user query into a search engine.

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Yu, Yang Xin. "Research of Information Retrieval Based on Web Page Segmentation." Applied Mechanics and Materials 204-208 (October 2012): 4928–31. http://dx.doi.org/10.4028/www.scientific.net/amm.204-208.4928.

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A Web information retrieval algorithm based on Web page segment is designed, the key idea of which is to segment each Web page into different topic areas or segments according to its HTML tags and contents since Web pages are semi-structure. First, the algorithm builds a HTML tag tree, and then it combines nodes in the tree under the rule of content similarity and visual similarity. During the process of retrieval and ranking, the algorithm makes full use of the segmentation information to sequence the relevant pages. The experimental results show that this method is able to improve the precision in search significantly and it is also a good reference for the design of the future search engines.

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Huang, Wei Zhong. "Research on Web Search Engine Optimization and its Application." Applied Mechanics and Materials 687-691 (November 2014): 1908–11. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1908.

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The universal search engine, which is widely used now, has significantly improved the efficiency of retrieving information. According to CNNIC (China Internet Network Information Center) 26th Internet survey, the search takes up 76.30% for absolute advantage as a major way for users to obtain information from the Internet. Among almost all the surveys of using on the Internet in the world, search engine is second only to e-mail service. But with the growth of a wide range of information, these universal search engines can not meet people's needs either in retrieval precision or in retrieval efficiency when retrieving information on a subject or topic. That's because as long as the user enters the same keywords, the feedbacks of universal search engine are just the same. Universal search engine does not take the differences in interests and needs between different users, which often exist, into account. For example, dentists and ceramics enthusiasts would hold different concerns about the term "ceramic". In order to be more rapid, accurate and efficient in retrieving information on particular subject or theme, it is essential to develop information retrieval systems on specific areas, that is, the domain-specific search engine.

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Lin, Zhi Chao, Lei Sun, and Xiao Liu. "Research and Improvement on Content-Based Web Search Engine." Advanced Materials Research 532-533 (June 2012): 1282–86. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.1282.

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There is a lot of information contained in the World Wide Web. It has become a research focus to obtain the required related resources quickly and accurately from the web through the content-based search engines. Most current tools of full text web search engine, such as Lucene which is a widely used open source retrieval library in information retrieval field, are purely keyword based. This may not sufficient for users to retrieve in the web. In this paper, we employ a method to overcome the limitations of current full text search engines in represent of Lucene. We propose a Query Expansion and Information Retrieval approach which can help users to acquire more accurate contents from the web. The Query Expansion component finds expanded candidate words of the query word through WordNet which contains synonyms in several different senses; In the Information Retrieval component, the query word and its candidate words are used together as the input of the search module to get the result items. Furthermore, we can put the result items into different classes based on the expansion. Some experiments and the results are described in the late part of this paper.

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Colaric, Susan M. "Instruction for Web Searching: An Empirical Study." College & Research Libraries 64, no. 2 (March 1, 2003): 111–22. http://dx.doi.org/10.5860/crl.64.2.111.

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Users searching the Web have difficulty using search engines and developing queries. Searches tend to be simple, and Boolean operators are used infrequently and incorrectly. Users also are unaware that search engines operate differently from other information retrieval systems. Yet, there is little research on effective instructional methods for teaching users how to search the Web. Research has looked at instructional methods for other types of information retrieval, but these systems differ a great deal from the Web. The purpose of this study was to determine what undergraduate students know about search engines and to examine instructional treatments to aid searchers in using a search engine.

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Sharma, Prem Sagar, and Divakar Yadav. "Incremental Refinement of Page Ranking of Web Pages." International Journal of Information Retrieval Research 10, no. 3 (July 2020): 57–73. http://dx.doi.org/10.4018/ijirr.2020070104.

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Web-based information retrieval systems called search engines have made things easy for information seekers, but still do not provide guarantees about the relevance of the information provided to the users. Information retrieval systems provide the information to the user based on certain retrieval criteria. Due to the large size of the WWW, it is very common that a large number of documents get identified related to a particular domain. Therefore, to help users towards finding the best matching documents, a ranking mechanism is employed by the search engine. In this article, an improved architecture for an information retrieval system is proposed. The proposed system makes a query log for each user query and stores the results retrieved to the user for that query. The system also provides relevant results by analyzing the content of the pages retrieved for the user query.

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Yari Zanganeh, Marzieh, and Nadjla Hariri. "The role of emotional aspects in the information retrieval from the web." Online Information Review 42, no. 4 (August 13, 2018): 520–34. http://dx.doi.org/10.1108/oir-04-2016-0121.

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Purpose The purpose of this paper is to identify the role of emotional aspects in information retrieval of PhD students from the web. Design/methodology/approach From the methodological perspective, the present study is experimental and the type of study is practical. The study population is PhD students of various fields of science. The study sample consists of 50 students as selected by the stratified purposive sampling method. The information aggregation is performed by observing the records of user’s facial expressions, log file by Morae software, as well as pre-search and post-search questionnaire. The data analysis is performed by canonical correlation analysis. Findings The findings showed that there was a significant relationship between emotional expressions and searchers’ individual characteristics. Searchers satisfaction of results, frequency internet search, experience of search, interest in the search task and familiarity with similar searches were correlated with the increased happy emotion. The examination of user’s emotions during searching performance showed that users with happiness emotion dedicated much time in searching and viewing of search solutions. More internet addresses with more queries were used by happy participants; on the other hand, users with anger and disgust emotions had the lowest attempt in search performance to complete search process. Practical implications The results imply that the information retrieval systems in the web should identify emotional expressions in a set of perceiving signs in human interaction with computer, similarity, face emotional states, searching and information retrieval from the web. Originality/value The results explicit in the automatic identification of users’ emotional expressions can enter new dimensions into their moderator and information retrieval systems on the web and can pave the way of design of emotional information retrieval systems for the successful retrieval of users of the network.

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Denecke, K. "An Architecture for Diversity-aware Search for Medical Web Content." Methods of Information in Medicine 51, no. 06 (2012): 549–56. http://dx.doi.org/10.3414/me11-02-0022.

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SummaryObjectives: The Web provides a huge source of information, also on medical and health-related issues. In particular the content of medical social media data can be diverse due to the background of an author, the source or the topic. Diversity in this context means that a document covers different aspects of a topic or a topic is described in different ways. In this paper, we introduce an approach that allows to consider the diverse aspects of a search query when providing retrieval results to a user.Methods: We introduce a system architecture for a diversity-aware search engine that allows retrieving medical information from the web. The diversity of retrieval results is assessed by calculating diversity measures that rely upon semantic information derived from a mapping to concepts of a medical terminology. Considering these measures, the result set is diversified by ranking more diverse texts higher.Results: The methods and system architecture are implemented in a retrieval engine for medical web content. The diversity measures reflect the diversity of aspects considered in a text and its type of information content. They are used for result presentation, filtering and ranking. In a user evaluation we assess the user satisfaction with an ordering of retrieval results that considers the diversity measures.Conclusions: It is shown through the evaluation that diversity-aware retrieval considering diversity measures in ranking could increase the user satisfaction with retrieval results.

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Chawla, Suruchi. "Intelligent Information Retrieval Using Hybrid of Fuzzy Set and Trust." Oriental journal of computer science and technology 10, no. 2 (April 19, 2017): 311–25. http://dx.doi.org/10.13005/ojcst/10.02.09.

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The main challenge for effective web Information Retrieval(IR) is to infer the information need from user’s query and retrieve relevant documents. The precision of search results is low due to vague and imprecise user queries and hence could not retrieve sufficient relevant documents. Fuzzy set based query expansion deals with imprecise and vague queries for inferring user’s information need. Trust based web page recommendations retrieve search results according to the user’s information need. In this paper an algorithm is designed for Intelligent Information Retrieval using hybrid of Fuzzy set and Trust in web query session mining to perform Fuzzy query expansion for inferring user’s information need and trust is used for recommendation of web pages according to the user’s information need. Experiment was performed on the data set collected in domains Academics, Entertainment and Sports and search results confirm the improvement of precision.

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Bond, Carol S. "Web users' information retrieval methods and skills." Online Information Review 28, no. 4 (August 1, 2004): 254–59. http://dx.doi.org/10.1108/14684520410553741.

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When trying to locate information on the Web people are faced with a variety of options. This research reviewed how a group of health related professionals approached the task of finding a named document. Most were eventually successful, but the majority encountered problems in their search techniques. Even experienced Web users had problems when working with a different interface to normal, and without access to their favourites. No relationship was found between the number of years' experience Web users had and the efficiency of their searching strategy. The research concludes that if people are to be able to use the Web quickly and efficiently as an effective information retrieval tool, as opposed to a recreational tool to surf the Internet, they need to have both an understanding of the medium and the tools, and the skills to use them effectively, both of which were lacking in the majority of participants in this study.

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Teixeira Lopes, Carla, and Cristina Ribeiro. "Comparative evaluation of web search engines in health information retrieval." Online Information Review 35, no. 6 (November 29, 2011): 869–92. http://dx.doi.org/10.1108/14684521111193175.

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Barathi. "Context Disambiguation Based Semantic Web Search for Effective Information Retrieval." Journal of Computer Science 7, no. 4 (April 1, 2011): 548–53. http://dx.doi.org/10.3844/jcssp.2011.548.553.

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Mahalakshmi, P., and N. Sabiyath Fathima. "An Art of Review on Conceptual based Information Retrieval." Webology 18, SI02 (January 13, 2021): 21–31. http://dx.doi.org/10.14704/web/v18si02/web18009.

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Basically keywords are used to index and retrieve the documents for the user query in a conventional information retrieval systems. When more than one keywords are used for defining the single concept in the documents and in the queries, inaccurate and incomplete results were produced by keyword based retrieval systems. Additionally, manual interventions are required for determining the relationship between the related keywords in terms of semantics to produce the accurate results which have paved the way for semantic search. Various research work has been carried out on concept based information retrieval to tackle the difficulties that are caused by the conventional keyword search and the semantic search systems. This paper aims at elucidating various representation of text that is responsible for retrieving relevant search results, approaches along with the evaluation that are carried out in conceptual information retrieval, the challenges faced by the existing research to expatiate requirements of future research. In addition, the conceptual information that are extracted from the different sources for utilizing the semantic representation by the existing systems have been discussed.

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Khurana, Dhiraj, and Cheshta Diwan. "GOVT_EXAM ONTOLOGY IN SEMANTIC WEB FOR QUERY RETRIEVAL." BSSS journal of computer 12, no. 1 (June 30, 2021): 22–29. http://dx.doi.org/10.51767/jc1203.

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The World wide web is growing day by day exponentially and it becomes difficult to find the relevant information even using efficient search engines. Search results always give lots of irrelevant data which often misled to actual needed information. One solution of this problem is semantic web which was proposed by Sir Tim Berner’s Lee. Semantic web is an extended version of World Wide Web that has opened the new doors for efficient information retrieval process. Ontology is one of the methodologies to implement the semantic web. In this paper govt exam ontology is created with the help of protégé ontology creation tool. In the given ontology various relationship between different govt exams of central and state level is provided and also the general information about these exams like exam type, subject level of exam and institutes for coaching is given. This domain specific ontology can help the potential information seeker to get the accurate information which can help to crack the exam.

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Wu, Minglei, and Jingchang Pan. "Analysis of character network heat based on web retrieval technology." ITM Web of Conferences 17 (2018): 03020. http://dx.doi.org/10.1051/itmconf/20181703020.

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Information technology is now developing rapidly, the Internet has also obtained widespread popularization. The amount of information on the network is increasing exponentially, whose information sources are widely distributed and varied. If the information can’t be managed in an orderly manner, it will be difficult for the user to extract the information they need from such a massive amount of information. Although the current search engine give people a lot of convenience in searching for information, but the search engine can’t reflect the user’s personalized information demand with facing a wide variety of users with different information needs, knowledge background and interest. In this paper, a recommendation method based on search results with java as a technology is implemented. This method takes Baidu hot people ranking as an example for verifying.

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Hahn, Trudi Bellardo. "Text Retrieval Online: Historical Perspective on Web Search Engines." Bulletin of the American Society for Information Science and Technology 24, no. 4 (January 31, 2005): 7–10. http://dx.doi.org/10.1002/bult.89.

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Buarki, Hanadi, and Bashaer Alkhateeb. "Use of hashtags to retrieve information on the web." Electronic Library 36, no. 2 (April 3, 2018): 286–304. http://dx.doi.org/10.1108/el-01-2017-0011.

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Purpose This paper aims to find out how people use hashtags as a medium of information retrieval and dissemination, and how they are used in social media tools, such as Instagram. Design/methodology/approach A quantitative question estimated the participants’ use of the hashtags during the workshop. Statistical data of the participants and their posts were collected from social network analysis tools. The posts that included the workshop’s designated hashtags were retrieved, recorded, coded and analysed to collect qualitative data. Findings In total, 74 (46 per cent) participants used the workshop’s hashtags to share posts, the retrieval of the hashtags declined by time and Google search engine retrieved the maximum results. It was found that a hashtag would be common when associated with descriptors, and that its use depends on its popularity, followers and its survival time. Finally, hashtags connect people, allow them to express their enthusiasm to reveal common interests and networks them through social media tools such as Instagram. Research limitations/implications The research limitations were in relation to the participants’ demographic information, the non-identification of their gender and hashtags being misspelt. Practical implications The research project summarises the experiences that social media has made connecting easier through the right use of hashtags by providing 24/7 free feedback, the possibility to exchange ideas and by their involvement in promoting and organising events. It also indicates interaction among people sharing the same interest by retrieving subject-based hashtags. Originality/value When retrieving information related to hashtags, it is recommended that multi-retrieval systems, social media tools and search engines should be consulted and not depend on a solo system or tool. Future research is recommended in search for a multi-retrieval social media and search engine tool that standardises the use of hashtags and will retrieve information from different platforms.

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Qian, Shuang Yan. "Design and Implementation of Landscape Plant Information Search Engine." Advanced Materials Research 971-973 (June 2014): 1892–96. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1892.

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With the explosive growth of the World Wide Web information, we need the appropriate retrieval tools, especially the retrieval of the professional information, we need a embody of search engines with the professional vocabulary features. Based on the research of search engine's core technology, this paper presents a design scheme which is the botanical garden plant information search engine based on Internet data, we descript of its design.

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Mahdi, Mohammed Najah, Abdul Rahim Ahmad, and Roslan Ismail. "Evaluating Search Results in Exploratory Search." International Journal of Engineering & Technology 7, no. 4.35 (November 30, 2018): 276. http://dx.doi.org/10.14419/ijet.v7i4.35.22746.

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The volume of information available on the World Wide Web is quite significant. This plethora of information has, to a large extent constantly challenged researchers in seeking for ways of making the information easily accessible to end users in as convenient ways as possible. Characteristically, ensuring the accessibility of this large amount of information involves three all-encompassing processes of retrieval, organization and presentation. The World Wide Web offers a platform for sharing information from large database repositories globally. However, information needs to be searched with specialized tools commonly referred to as search engines. While a number of search engines does presently exist, most of these search engines are noted for their inability to retrieve information usable to the end user. It is therefore critical for the results generated from search engines to be intelligently organized for the optimal usefulness of the information to the searcher. Exploratory web technologies is capable of filing this gap. Therefore, this paper reviews exploratory search as a mechanism for conducting result-oriented search. It also reviews the ways of evaluating the search results obtained from an exploratory search.

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Lewandowski, Dirk. "The retrieval effectiveness of web search engines: considering results descriptions." Journal of Documentation 64, no. 6 (October 17, 2008): 915–37. http://dx.doi.org/10.1108/00220410810912451.

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Rogushina, J. V. "Classification of means and methods of the Web semantic retrieval." PROBLEMS IN PROGRAMMING, no. 1 (2017): 030–50. http://dx.doi.org/10.15407/pp2017.01.030.

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Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

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K.G., Srinivasa, Anil Kumar Muppalla, Bharghava Varun A., and Amulya M. "MapReduce Based Information Retrieval Algorithms for Efficient Ranking of Webpages." International Journal of Information Retrieval Research 1, no. 4 (October 2011): 23–37. http://dx.doi.org/10.4018/ijirr.2011100102.

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In this paper, the authors discuss the MapReduce implementation of crawler, indexer and ranking algorithms in search engines. The proposed algorithms are used in search engines to retrieve results from the World Wide Web. A crawler and an indexer in a MapReduce environment are used to improve the speed of crawling and indexing. The proposed ranking algorithm is an iterative method that makes use of the link structure of the Web and is developed using MapReduce framework to improve the speed of convergence of ranking the WebPages. Categorization is used to retrieve and order the results according to the user choice to personalize the search. A new score is introduced in this paper that is associated with each WebPage and is calculated using user’s query and number of occurrences of the terms in the query in the document corpus. The experiments are conducted on Web graph datasets and the results are compared with the serial versions of crawler, indexer and ranking algorithms.

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Srinivasa, K. G., N. Pramod, K. R. Venugopal, and L. M. Patnaik. "Effects of Information Filters." International Journal of Information Retrieval Research 2, no. 2 (April 2012): 1–12. http://dx.doi.org/10.4018/ijirr.2012040101.

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In the Internet era, information processing for personalization and relevance has been one of the key topics of research and development. It ranges from design of applications like search engines, web crawlers, learning engines to reverse image searches, audio processed search, auto complete, etc. Information retrieval plays a vital role in most of the above mentioned applications. A part of information retrieval which deals with personalization and rendering is often referred to as Information Filtering. The emphasis of this paper is to empirically analyze the information filters commonly seen and to analyze their correctness and effects. The measure of correctness is not in terms of percentage of correct results but instead a rational approach of analysis using a non mathematical argument is presented. Filters employed by Google’s search engine are used to analyse the effects of filtering on the web. A plausible solution to the errors of filtering phenomenon is also discussed.

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Kong, Shao Ying, and Hong Liang Guo. "Research on Intelligent Information Retrieval Based on Semantic Web Technology." Applied Mechanics and Materials 380-384 (August 2013): 2075–78. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.2075.

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According to the rapid development of the Internet and the increase of the network resources, it was very important to search the information resources for meeting the need of large ground of users. The key words were used as the indexes for retrieval with traditional method. But it couldnt reflect the real purposes and intentions of the users precisely. An improved information retrieval method based on the semantic web technology was proposed for carrying out the information retrieval work precisely and effectively. The mew retrieval system was not just recognizing the words simply, but it could comprehend the semantic ingredients of the words and sentences. The semantic web retrieval system was constructed eventually. Comparing to the traditional keywords retrieval method, the similarity degree was calculated in the simulation, simulation result shows that the retrieval precision ratio of new method increases by 15%, then the intelligent, efficient and accurate information retrieval system is realized successfully.

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Zhang, Yu Yan. "A Retrieval Sorting Approach for Online Forums Based on Domain Topics." Advanced Materials Research 756-759 (September 2013): 2152–56. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2152.

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Topical search engine is an extension of general-purpose search engines, which has become an important research subject in Web information retrieval recently. Focusing on the development of Web 2.0 applications, a result ranking approach is proposed on the basis of LDA model to rank the search results from Web forums. Compared with traditional methods, this approach takes up less storage space, and can more quickly and accurately respond to user inquiries. This work has important significance for the research of improving the performance of retrieval results of web forums.

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France, Tim, Dave Yen, Jyun‐Cheng Wang, and Chia‐Ming Chang. "Integrating search engines with data mining for customer‐oriented information search." Information Management & Computer Security 10, no. 5 (December 1, 2002): 242–54. http://dx.doi.org/10.1108/09685220210446597.

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In recent years, the World Wide Web (WWW) has become incredibly popular in homes and offices alike. Consumers need to search for relevant information to help solve purchasing problems on various Web sites. Although there is no question that great numbers of WWW users will continue using search engines for information retrieval, consumers still hesitate before making a final decision, often because only rough and limited information about the products is made available. Consequently, consumers need the help of data mining in order to help them make informed decisions. Herein we propose a new approach to integrating a search engine with data mining in an effort to help support customer‐oriented information search action. This approach also illustrates how to reduce the consumer’s information search perplexity.

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Sen, Procheta. "Proactive information retrieval." ACM SIGIR Forum 55, no. 2 (December 2021): 1–2. http://dx.doi.org/10.1145/3527546.3527576.

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Users interact with digital systems with some underlying tasks in their minds. In our research scope, a task can be either single or multi-staged. A single-staged task is associated with a single information need, whereas a multi-staged one is associated with more than one information needs. An example of a single-staged task is suggesting related papers to an author while they are writing a section of the research papers. An example of a multi-staged task is planning for a vacation, where the different underlying information needs could be 'places to visit', 'booking accommodation' etc. In the process of accomplishing their task objectives, a user often needs to interact with an information retrieval (IR) system to address one or more information needs. For instance, for writing a research paper on a chosen topic, a user needs to look for existing research work related to the topic. Traditional IR systems do not take into account a user's task intent while showing search results to the user. In our work, we propose a methodology towards developing next generation IR systems (i.e. proactive IR systems) which seek to anticipate the task intent of a user from their interactions with digital systems in order to proactively suggest potentially relevant information sources to assist them to complete their tasks. Specifically speaking, in this PhD, we proposed an embedding approach that captures the task semantics from the interactions of a user with a digital system (e.g. laptop, desktop, smartphone etc.). The proposed embedding approach is then applied for the downstream tasks of providing proactive suggestions in both single and multi staged scenarios. For the single-staged task, we propose a simulation setup to simulate a user's reading and writing interactions in a desktop environment. For the multi-staged task, we focus on web search sessions where a user can have multiple information needs corresponding to a search task. We also proposed a reproducible evaluation framework to compare between different proactive suggestion models. Awarded by : Dublin City University, Ireland on 10 August 2021. Supervised by : Gareth Jones. Available at : https://procheta.github.io/sprocheta/Thesis.pdf.

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., Yagnesh D. Dave. "COMPARATIVE ANALYSIS OF RELATIVE AND EXACT SEARCH FOR WEB INFORMATION RETRIEVAL." International Journal of Research in Engineering and Technology 04, no. 09 (September 25, 2015): 136–41. http://dx.doi.org/10.15623/ijret.2015.0409025.

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Behnert, Christiane, and Dirk Lewandowski. "A framework for designing retrieval effectiveness studies of library information systems using human relevance assessments." Journal of Documentation 73, no. 3 (May 8, 2017): 509–27. http://dx.doi.org/10.1108/jd-08-2016-0099.

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Purpose The purpose of this paper is to demonstrate how to apply traditional information retrieval (IR) evaluation methods based on standards from the Text REtrieval Conference and web search evaluation to all types of modern library information systems (LISs) including online public access catalogues, discovery systems, and digital libraries that provide web search features to gather information from heterogeneous sources. Design/methodology/approach The authors apply conventional procedures from IR evaluation to the LIS context considering the specific characteristics of modern library materials. Findings The authors introduce a framework consisting of five parts: search queries, search results, assessors, testing, and data analysis. The authors show how to deal with comparability problems resulting from diverse document types, e.g., electronic articles vs printed monographs and what issues need to be considered for retrieval tests in the library context. Practical implications The framework can be used as a guideline for conducting retrieval effectiveness studies in the library context. Originality/value Although a considerable amount of research has been done on IR evaluation, and standards for conducting retrieval effectiveness studies do exist, to the authors’ knowledge this is the first attempt to provide a systematic framework for evaluating the retrieval effectiveness of twenty-first-century LISs. The authors demonstrate which issues must be considered and what decisions must be made by researchers prior to a retrieval test.

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Chawla, Suruchi. "Application of Fuzzy C-Means Clustering and Semantic Ontology in Web Query Session Mining for Intelligent Information Retrieval." International Journal of Fuzzy System Applications 10, no. 1 (January 2021): 1–19. http://dx.doi.org/10.4018/ijfsa.2021010101.

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Information retrieval based on keywords search retrieves irrelevant documents because of vocabulary gap between document content and search queries. The keyword vector representation of web documents is very high dimensional, and keyword terms are unable to capture the semantic of document content. Ontology has been built in various domains for representing the semantics of documents based on concepts relevant to document subject. The web documents often contain multiple topics; therefore, fuzzy c-means document clustering has been used for discovering clusters with overlapping boundaries. In this paper, the method is proposed for intelligent information retrieval using hybrid of fuzzy c-means clustering and ontology in query session mining. Thus, use of fuzzy clusters of web query session concept vector improve quality of clusters for effective web search. The proposed method was evaluated experimentally, and results show the improvement in precision of search results.

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DI SCIASCIO, EUGENIO, FRANCESCO M. DONINI, and MARINA MONGIELLO. "USING COMPUTATION TREE LOGIC FOR INTELLIGENT INFORMATION SEARCH ON THE WEB." International Journal of Computational Intelligence and Applications 02, no. 03 (September 2002): 245–53. http://dx.doi.org/10.1142/s1469026802000579.

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Web engines crawl hyperlinks to search for new documents; yet when they index discovered documents they basically revert to conventional information retrieval models and concentrate on the indexing of terms in a single document. We propose to overcome such limits with an approach based on temporal logic. By modeling a web site as a finite state transition system we are able to define complex and selective queries over hyperlinks with the aid of Computation Tree Logic operators. We deployed the proposed approach in a prototype system that allows users pose queries in natural language. Queries are automatically translated in Computation Tree Logic, and the answer returned by our system is a set of paths. Experiments carried out with the aid of human experts show improved retrieval effectiveness with respect to current search engines.

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Agbele, Kehinde, Ademola Adesina, Daniel Ekong, and Oluwafemi Ayangbekun. "State-of-the-Art Review on Relevance of Genetic Algorithm to Internet Web Search." Applied Computational Intelligence and Soft Computing 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/152385.

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People use search engines to find information they desire with the aim that their information needs will be met. Information retrieval (IR) is a field that is concerned primarily with the searching and retrieving of information in the documents and also searching the search engine, online databases, and Internet. Genetic algorithms (GAs) are robust, efficient, and optimizated methods in a wide area of search problems motivated by Darwin’s principles of natural selection and survival of the fittest. This paper describes information retrieval systems (IRS) components. This paper looks at how GAs can be applied in the field of IR and specifically the relevance of genetic algorithms to internet web search. Finally, from the proposals surveyed it turns out that GA is applied to diverse problem fields of internet web search.

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Telemala, Joseph P., and Hussein Suleman. "Exploring Topic-language Preferences in Multilingual Swahili Information Retrieval in Tanzania." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 6 (November 30, 2021): 1–30. http://dx.doi.org/10.1145/3458671.

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Habitual switching of languages is a common behaviour among polyglots when searching for information on the Web. Studies in information retrieval (IR) and multilingual information retrieval (MLIR) suggest that part of the reason for such regular switching of languages is the topic of search. Unlike survey-based studies, this study uses query and click-through logs. It exploits the querying and results selection behaviour of Swahili MLIR system users to explore how topic of search (query) is associated with language preferences—topic-language preferences. This article is based on a carefully controlled study using Swahili-speaking Web users in Tanzania who interacted with a guided multilingual search engine. From the statistical analysis of queries and click-through logs, it was revealed that language preferences may be associated with the topics of search. The results also suggest that language preferences are not static; they vary along the course of Web search from query to results selection. In most of the topics, users either had significantly no language preference or preferred to query in Kiswahili and changed their preference to either English or no preference for language when selecting/clicking on the results. The findings of this study might provide researchers with more insights in developing better MLIR systems that support certain types of users and in certain scenarios.

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Journal articles on the topic '080704 Information Retrieval and Web Search'

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