Relevant bibliographies by topics / 080704 Information Retrieval and Web Search

Academic literature on the topic '080704 Information Retrieval and Web Search'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "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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Dissertations / Theses on the topic "080704 Information Retrieval and Web Search"

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Tjondronegoro, Dian W. "PhD Thesis: "Content-based Video Indexing for Sports Applications using Multi-modal approach"." Thesis, Deakin University, 2005. https://eprints.qut.edu.au/2199/1/PhDThesis_Tjondronegoro.pdf.

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Triggered by technology innovations, there has been a huge increase in the utilization of video, as one of the most preferred types of media due to its content richness, for many significant applications. To sustain an ongoing rapid growth of video information, there is an emerging demand for a sophisticated content-based video indexing system. However, current video indexing solutions are still immature and lack of any standard. One solution, namely annotation-based indexing, allows video retrieval using textual annotations. However, the major limitations are the restrictions of pre-defined keywords that can be used and the expensive manual work on annotating video. Another solution called feature-based indexing allows video search by low-level features comparison such as query by a sample image. Even though this approach can use automatically extracted features, users would not be able to retrieve video intuitively, based on high-level concepts. This predicament is caused by the so-called semantic gap which highlights the fact that users recall video contents in a high-level abstraction while video is generally stored as an arbitrary sequence of audio-visual tracks. To bridge the semantic gap, this thesis will demonstrate the use of domain-specific approach which aims to utilize domain knowledge in facilitating the extraction of high-level concepts directly from the audiovisual features. The main idea behind domain-specific approach is the use of domain knowledge to guide the integration of features from multi-modal tracks. For example, to extract goal segments from soccer and basketball video, slow motion replay scenes (visual) and excitement (audio) should be detected as they are played during most goal segments. Domain-specific indexing also exploits specific browsing and querying methods which are driven by specific users/applications’ requirements. Sports video is selected as the primary domain due to its content richness and popularity. Moreover, broadcasted sports videos generally span for hours with many redundant activities and the key segments could make up only 30% to 60% of the entire data depending on the progress of the match. This thesis presents a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple (audio-visual) modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s). The main objective is to contribute to the three major components of sports video indexing systems. The first component is a set of powerful techniques to extract audio-visual features and semantic contents automatically. The main purposes are to reduce manual annotations and to summarize the lengthy contents into a compact, meaningful and more enjoyable presentation. The second component is an expressive and flexible indexing technique that supports gradual index construction. Indexing scheme is essential to determine the methods by which users can access a video database. The third and last component is a query language that can generate dynamic video summaries for smart browsing and support user-oriented retrievals.
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Lewandowski, Dirk. "Web Searching, Search Engines and Information Retrieval." ISO Press, 2005. http://hdl.handle.net/10150/106395.

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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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Craswell, Nicholas Eric, and Nick Craswell@anu edu au. "Methods for Distributed Information Retrieval." The Australian National University. Faculty of Engineering and Information Technology, 2001. http://thesis.anu.edu.au./public/adt-ANU20020315.142540.

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Published methods for distributed information retrieval generally rely on cooperation from search servers. But most real servers, particularly the tens of thousands available on the Web, are not engineered for such cooperation. This means that the majority of methods proposed, and evaluated in simulated environments of homogeneous cooperating servers, are never applied in practice. ¶ This thesis introduces new methods for server selection and results merging. The methods do not require search servers to cooperate, yet are as effective as the best methods which do. Two large experiments evaluate the new methods against many previously published methods. In contrast to previous experiments they simulate a Web-like environment, where servers employ varied retrieval algorithms and tend not to sub-partition documents from a single source. ¶ The server selection experiment uses pages from 956 real Web servers, three different retrieval systems and TREC ad hoc topics. Results show that a broker using queries to sample servers’ documents can perform selection over non-cooperating servers without loss of effectiveness. However, using the same queries to estimate the effectiveness of servers, in order to favour servers with high quality retrieval systems, did not consistently improve selection effectiveness. ¶ The results merging experiment uses documents from five TREC sub-collections, five different retrieval systems and TREC ad hoc topics. Results show that a broker using a reference set of collection statistics, rather than relying on cooperation to collate true statistics, can perform merging without loss of effectiveness. Since application of the reference statistics method requires that the broker download the documents to be merged, experiments were also conducted on effective merging based on partial documents. The new ranking method developed was not highly effective on partial documents, but showed some promise on fully downloaded documents. ¶ Using the new methods, an effective search broker can be built, capable of addressing any given set of available search servers, without their cooperation.
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Costa, Miguel. "SIDRA: a Flexible Web Search System." Master's thesis, Department of Informatics, University of Lisbon, 2004. http://hdl.handle.net/10451/13914.

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Sidra is a new indexing, searching and ranking system for Web contents. It has a flexible, parallel, distributed and scalable architecture. Sidra maintains several data structures that provide multiple access methods to different data dimensions, giving it the capability to select results reflecting search contexts. Its design addresses current challenges of Web search engines: high performance, short searching and indexing times, good quality of results, scalability and high service availability
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Limbu, Dilip Kumar. "Contextual information retrieval from the WWW." Click here to access this resource online, 2008. http://hdl.handle.net/10292/450.

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Contextual information retrieval (CIR) is a critical technique for today’s search engines in terms of facilitating queries and returning relevant information. Despite its importance, little progress has been made in its application, due to the difficulty of capturing and representing contextual information about users. This thesis details the development and evaluation of the contextual SERL search, designed to tackle some of the challenges associated with CIR from the World Wide Web. The contextual SERL search utilises a rich contextual model that exploits implicit and explicit data to modify queries to more accurately reflect the user’s interests as well as to continually build the user’s contextual profile and a shared contextual knowledge base. These profiles are used to filter results from a standard search engine to improve the relevance of the pages displayed to the user. The contextual SERL search has been tested in an observational study that has captured both qualitative and quantitative data about the ability of the framework to improve the user’s web search experience. A total of 30 subjects, with different levels of search experience, participated in the observational study experiment. The results demonstrate that when the contextual profile and the shared contextual knowledge base are used, the contextual SERL search improves search effectiveness, efficiency and subjective satisfaction. The effectiveness improves as subjects have actually entered fewer queries to reach the target information in comparison to the contemporary search engine. In the case of a particularly complex search task, the efficiency improves as subjects have browsed fewer hits, visited fewer URLs, made fewer clicks and have taken less time to reach the target information when compared to the contemporary search engine. Finally, subjects have expressed a higher degree of satisfaction on the quality of contextual support when using the shared contextual knowledge base in comparison to using their contextual profile. These results suggest that integration of a user’s contextual factors and information seeking behaviours are very important for successful development of the CIR framework. It is believed that this framework and other similar projects will help provide the basis for the next generation of contextual information retrieval from the Web.
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Morrison, Patrick Jason. "Tagging and Searching: Search Retrieval Effectiveness of Folksonomies on the Web." [Kent, Ohio] : Kent State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=kent1177305096.

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Thesis (M.S.)--Kent State University, 2007.
Title from PDF t.p. (viewed July 2, 2007). Advisor: David B. Robins. Keywords: information retrieval, search engine, social bookmarking, tagging, folksonomy, Internet, World Wide Web. Includes survey instrument. Includes bibliographical references (p. 137-141).
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Nguyen, Qui V. "Enhancing a Web Crawler with Arabic Search." Thesis, Monterey, California: Naval Postgraduate School, 2012.

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Many advantages of the Internetâ ease of access, limited regulation, vast potential audience, and fast flow of informationâ have turned it into the most popular way to communicate and exchange ideas. Criminal and terrorist groups also use these advantages to turn the Internet into their new play/battle fields to conduct their illegal/terror activities. There are millions of Web sites in different languages on the Internet, but the lack of foreign language search engines makes it impossible to analyze foreign language Web sites efficiently. This thesis will enhance an open source Web crawler with Arabic search capability, thus improving an existing social networking tool to perform page correlation and analysis of Arabic Web sites. A social networking tool with Arabic search capabilities could become a valuable tool for the intelligence community. Its page correlation and analysis results could be used to collect open source intelligence and build a network of Web sites that are related to terrorist or criminal activities.
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Tsukuda, Kosetsu. "A Study on Web Search and Analysis based on Typicality." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/192217.

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Umemoto, Kazutoshi. "A Study on Fine-Grained User Behavior Analysis in Web Search." 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/215679.

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Halpin, Harry. "Sense and reference on the Web." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/3796.

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This thesis builds a foundation for the philosophy of theWeb by examining the crucial question: What does a Uniform Resource Identifier (URI) mean? Does it have a sense, and can it refer to things? A philosophical and historical introduction to the Web explains the primary purpose of theWeb as a universal information space for naming and accessing information via URIs. A terminology, based on distinctions in philosophy, is employed to define precisely what is meant by information, language, representation, and reference. These terms are then employed to create a foundational ontology and principles ofWeb architecture. From this perspective, the SemanticWeb is then viewed as the application of the principles of Web architecture to knowledge representation. However, the classical philosophical problems of sense and reference that have been the source of debate within the philosophy of language return. Three main positions are inspected: the logicist position, as exemplified by the descriptivist theory of reference and the first-generation SemanticWeb, the direct reference position, as exemplified by Putnamand Kripke’s causal theory of reference and the second-generation Linked Data initiative, and a Wittgensteinian position that views the Semantic Web as yet another public language. After identifying the public language position as the most promising, a solution of using people’s everyday use of search engines as relevance feedback is proposed as a Wittgensteinian way to determine sense of URIs. This solution is then evaluated on a sample of the Semantic Web discovered by via using queries from a hypertext search engine query log. The results are evaluated and the technique of using relevance feedback from hypertext Web searches to determine relevant Semantic Web URIs in response to user queries is shown to considerably improve baseline performance. Future work for the Web that follows from our argument and experiments is detailed, and outlines of a future philosophy of the Web laid out.
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Books on the topic "080704 Information Retrieval and Web Search"

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Ceri, Stefano. Search Computing: Broadening Web Search. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Francesco, Guerra, Velegrakis Yannis, and SpringerLink (Online service), eds. Semantic Search over the Web. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Carmel, David. Estimating the query difficulty for information retrieval. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2010.

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Making search work: Implementing Web, intranet, and enterprise search. London, England: Facet, 2007.

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Faceted search. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2009.

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Dovey, Steven. Information retrieval on the World Wide Web: Search engines and subject indexes. Loughborough: Loughborough University, 1996.

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Abramowicz, Witold. Knowledge-Based Information Retrieval and Filtering from the Web. Boston, MA: Springer US, 2003.

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Chang, George. Mining the World Wide Web: An Information Search Approach. Boston, MA: Springer US, 2001.

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Shi, China) INGS 2008 (2008 Shenyang. INGS 2008: 2008 International Workshop on Information-Explosion and Next Generation Search : proceedings, 26-27 April 2008, Shenyang, China. Los Alamitos, Calif: IEEE Computer Society, 2008.

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George, Chang, ed. Mining the World Wide Web: An information search approach. Boston: Kluwer Academic, 2001.

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Book chapters on the topic "080704 Information Retrieval and Web Search"

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Sha, Chaofeng, Keqiang Wang, Dell Zhang, Xiaoling Wang, and Aoying Zhou. "Optimizing Top-k Retrieval: Submodularity Analysis and Search Strategies." In Web-Age Information Management, 18–29. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08010-9_3.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Meta-search and Multi-domain Search." In Web Information Retrieval, 161–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_11.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Semantic Search." In Web Information Retrieval, 181–206. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_12.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Multimedia Search." In Web Information Retrieval, 207–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_13.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Search Engines." In Web Information Retrieval, 71–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_6.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Advertising in Search." In Web Information Retrieval, 121–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_9.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Search Process and Interfaces." In Web Information Retrieval, 223–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_14.

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Ceri, Stefano, Alessandro Bozzon, Marco Brambilla, Emanuele Della Valle, Piero Fraternali, and Silvia Quarteroni. "Natural Language Processing for Search." In Web Information Retrieval, 57–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39314-3_5.

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Liu, Bing. "Information Retrieval and Web Search." In Web Data Mining, 211–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19460-3_6.

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Ting-Xuan, Wang, and Lu Wen-Hsiang. "Identifying Popular Search Goals behind Search Queries to Improve Web Search Ranking." In Information Retrieval Technology, 250–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25631-8_23.

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Conference papers on the topic "080704 Information Retrieval and Web Search"

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Limbu, Dilip K., Andrew M. Connor, Russel Pears, and Stephen G. MacDonell. "Improving Web Search Using Contextual Retrieval." In 2009 Sixth International Conference on Information Technology: New Generations. IEEE, 2009. http://dx.doi.org/10.1109/itng.2009.133.

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Abdullah, Noryusliza, and Rosziati Ibrahim. "Knowledge retrieval using hybrid semantic web search." In 2012 International Conference on Computer & Information Science (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccisci.2012.6297213.

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Vtyurina, Alexandra. "Towards Non-Visual Web Search." In CHIIR '19: Conference on Human Information Interaction and Retrieval. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3295750.3298976.

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"DOES CAPITALIZATION MATTER IN WEB SEARCH?" In International Conference on Knowledge Discovery and Information Retrieval. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0003102503020306.

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Hoeber, Orland. "Web Information Retrieval Support Systems: The Future of Web Search." In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2008. http://dx.doi.org/10.1109/wiiat.2008.151.

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Wei, Wang, Payam M. Barnaghi, and Andrzej Bargiela. "Semantic-Enhanced Information Search and Retrieval." In Sixth International Conference on Advanced Language Processing and Web Information Technology (ALPIT 2007). IEEE, 2007. http://dx.doi.org/10.1109/alpit.2007.59.

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Collins-Thompson, Kevyn, Soo Young Rieh, Carl C. Haynes, and Rohail Syed. "Assessing Learning Outcomes in Web Search." In CHIIR '16: Conference on Human Information Interaction and Retrieval. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2854946.2854972.

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"Guided Exploratory Search on the Mobile Web." In International Conference on Knowledge Discovery and Information Retrieval. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0004135900650074.

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Huang, Jimmy. "Search beyond Traditional Probabilistic Information Retrieval." In 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2011. http://dx.doi.org/10.1109/wi-iat.2011.295.

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Sumalatha, M. R., V. Vaidehi, A. Kannan, and S. Anandhi. "Information Retrieval using Semantic Web Browser - Personalized and Categorical Web Search." In 007 International Conference on Signal Processing, Communications and Networking. IEEE, 2007. http://dx.doi.org/10.1109/icscn.2007.350738.

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Reports on the topic "080704 Information Retrieval and Web Search"

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Qu, Pengda, Jing Huang, Shiqi Wang, Size Li, Qian Hu, Wei Wang, and Xiaohu Tang. Efficacy and safety of modified Ermiao decoction in the treatment of gouty arthritis: A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, July 2022. http://dx.doi.org/10.37766/inplasy2022.7.0063.

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Review question / Objective: The purpose of this study is to comprehensively evaluate the efficacy and safety of modified Ermiao decoction in the treatment of gouty arthritis. Information sources: We will conduct searches of Web of Science, PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform (Wanfang), Weipu Chinese Science and Technology Journal Full-text Database (VIP), and Chinese Biomedical Literature Database (CBM) from their inception to July 2022. In addition, trial registration platforms will also be searched for ongoing or unpublished trials, including International Clinical Trials Registry Platform and Chinese Clinical Trial Registry Centre. The languages of included studies will be restricted in English and Chinese. Medical Subject Headings and free words terms will be used during the retrieval process. The main search terms include “gouty arthritis”, “modified Ermiao”, and “randomized controlled trial.” A draft of the PubMed search strategy is included in Table 1. Similar retrieval strategies will be applied to the other databases mentioned above. We will also search for relevant systematic reviews of using MED for GA and reference lists of eligible studies to improve recall ratio.
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