Journal articles: 'Federated search'

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Shokouhi, Milad, and Luo Si. "Federated Search." Foundations and Trends® in Information Retrieval 5, no. 1 (2011): 1–102. http://dx.doi.org/10.1561/1500000010.

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Boss, Stephen C., and Michael L. Nelson. "Federated Search Tools." Reference Librarian 44, no. 91-92 (October 26, 2005): 139–60. http://dx.doi.org/10.1300/j120v44n91_10.

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S Lingam, Arunadevi. "Federated search and discovery solutions." IP Indian Journal of Library Science and Information Technology 5, no. 1 (July 15, 2020): 39–42. http://dx.doi.org/10.18231/j.ijlsit.2020.008.

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Arguello, Jaime. "Federated search in heterogeneous environments." ACM SIGIR Forum 46, no. 1 (May 20, 2012): 78–79. http://dx.doi.org/10.1145/2215676.2215686.

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Rainwater, Jean. "Maintaining a Federated Search Service." Internet Reference Services Quarterly 12, no. 3-4 (September 20, 2007): 309–23. http://dx.doi.org/10.1300/j136v12n03_05.

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Schatz, B., W. Mischo, T. Cole, A. Bishop, S. Harum, E. Johnson, L. Neumann, Hsinchun Chen, and Dorbin Ng. "Federated search of scientific literature." Computer 32, no. 2 (1999): 51–59. http://dx.doi.org/10.1109/2.745720.

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Woods, Roberta F. "From Federated Search to the Universal Search Solution." Serials Librarian 58, no. 1-4 (April 2010): 141–48. http://dx.doi.org/10.1080/03615261003622957.

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Belden, J., J. Williams, B. Richardson, K. Schuster, and D. Saparova. "Evaluating a federated medical search engine." Applied Clinical Informatics 05, no. 03 (2014): 731–45. http://dx.doi.org/10.4338/aci-2014-03-ra-0021.

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SummaryBackground: Federated medical search engines are health information systems that provide a single access point to different types of information. Their efficiency as clinical decision support tools has been demonstrated through numerous evaluations. Despite their rigor, very few of these studies report holistic evaluations of medical search engines and even fewer base their evaluations on existing evaluation frameworks.Objectives: To evaluate a federated medical search engine, MedSocket, for its potential net benefits in an established clinical setting.Methods: This study applied the Human, Organization, and Technology (HOT-fit) evaluation framework in order to evaluate MedSocket. The hierarchical structure of the HOT-factors allowed for identification of a combination of efficiency metrics. Human fit was evaluated through user satisfaction and patterns of system use; technology fit was evaluated through the measurements of time-on-task and the accuracy of the found answers; and organization fit was evaluated from the perspective of system fit to the existing organizational structure.Results: Evaluations produced mixed results and suggested several opportunities for system improvement. On average, participants were satisfied with MedSocket searches and confident in the accuracy of retrieved answers. However, MedSocket did not meet participants’ expectations in terms of download speed, access to information, and relevance of the search results. These mixed results made it necessary to conclude that in the case of MedSocket, technology fit had a significant influence on the human and organization fit. Hence, improving technological capabilities of the system is critical before its net benefits can become noticeable.Conclusions: The HOT-fit evaluation framework was instrumental in tailoring the methodology for conducting a comprehensive evaluation of the search engine. Such multidimensional evaluation of the search engine resulted in recommendations for system improvement.Citation: Saparova D, Belden J, Williams J, Richardson B, Schuster K. Evaluating a federated medical search engine: Tailoring the methodology and reporting the evaluation outcomes. Appl Clin Inf 2014; 5: 731–745http://dx.doi.org/10.4338/ACI-2014-03-RA-0021

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Lederman, Abe. "An architecture for scaling federated search." Proceedings of the American Society for Information Science and Technology 46, no. 1 (2009): 1–4. http://dx.doi.org/10.1002/meet.2009.1450460342.

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Deshmukh, Shamkant, Sonia Bhavsar, and Sandeep Bhavsar. "Open Source Software for Federated Search." DESIDOC Journal of Library & Information Technology 32, no. 5 (September 1, 2012): 427–30. http://dx.doi.org/10.14429/djlit.32.5.2653.

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Si, Luo. "Federated search of text search engines in uncooperative environments." ACM SIGIR Forum 41, no. 1 (June 2007): 120. http://dx.doi.org/10.1145/1273221.1273232.

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Bracke, Paul J., David K. Howse, and Samuel M. Keim. "Evidence-based Medicine Search: a customizable federated search engine." Journal of the Medical Library Association : JMLA 96, no. 2 (April 2008): 108–13. http://dx.doi.org/10.3163/1536-5050.96.2.108.

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Gore, Genevieve. "Undergraduates Prefer Federated Searching to Searching Databases Individually." Evidence Based Library and Information Practice 3, no. 3 (September 3, 2008): 61. http://dx.doi.org/10.18438/b8b318.

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A Review of: Belliston, C. Jeffrey, Jared L. Howland, & Brian C. Roberts. “Undergraduate Use of Federated Searching: A Survey of Preferences and Perceptions of Value-Added Functionality.” College & Research Libraries 68.6 (Nov. 2007): 472-86. Objective – To determine whether use of federated searching by undergraduates saves time, meets their information needs, is preferred over searching databases individually, and provides results of higher quality. Design – Crossover study. Setting – Three American universities, all members of the Consortium of Church Libraries & Archives (CCLA): BYU (Brigham Young University, a large research university); BYUH (Brigham Young University – Hawaii, a small baccalaureate college); and BYUI (Brigham Young University – Idaho, a large baccalaureate college) Subjects – Ninety-five participants recruited via e-mail invitations sent to a random sample of currently enrolled undergraduates at BYU, BYUH, and BYUI. Methods – Participants were given written directions to complete a literature search for journal articles on two biology-related topics using two search methods: 1. federated searching with WebFeat® (implemented in the same way for this study at the three universities) and 2. a hyperlinked list of databases to search individually. Both methods used the same set of seven databases. Each topic was assigned in random order to one of the two search methods, also assigned in random order, for a total of two searches per participant. The time to complete the searches was recorded. Students compiled their list of citations, which were later normalized and graded. To analyze the quality of the citations, one quantitative rubric was created by librarians and one qualitative rubric was approved by a faculty member at BYU. The librarian-created rubric included the journal impact factor (from ISI’s Journal Citation Reports®), the proportion of citations from peer-reviewed journals (determined from Ulrichsweb.com™) to total citations, and the timeliness of the articles. The faculty-approved rubric included three criteria: relevance to the topic, quality of the individual citations (good quality: primary research results, peer-reviewed sources), and number of citations. Data were then analysed using ANOVA and MANOVA. Finally, librarians at the ACRL 13th National Conference Presentation were polled about their perceptions of the time savings of federated searching, whether the method meets undergraduates’ information needs, undergraduate preference for searching, and the quality of citations found. Main Results – Seventy percent of all participants preferred federated searching. For all schools combined, there was no statistically significant difference between the average time taken using federated searching (20.34 minutes) vs. non-federated searching (22.72 minutes). For all schools combined, there was a statistically significant difference in satisfaction of results favouring federated searching (5.59/7 vs. 4.80/7 for non-federated searching, α = .05). According to the librarian-created rubric, citations retrieved from federated searching were a statistically significant 6% lower in quality than citations retrieved from non-federated searching (α = .05). The faculty-approved rubric did not detect a difference in the quality of the citations retrieved using the 2 methods. Librarians’ perceptions as assessed at the ACRL 13th National Conference Presentation generally matched the authors’ findings. Conclusion – Overall, students in this study preferred federated searching, were more satisfied with the results of federated searching, and saved time (although the savings were not statistically significant). The quality of citations retrieved via both methods was judged to be similar. The study provides useful information for librarians interested in users’ experiences and perceptions of federated searching, and indicates future studies worth conducting.

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Caswell, Jerry V., and John D. Wynstra. "Improving the search experience: federated search and the library gateway." Library Hi Tech 28, no. 3 (September 7, 2010): 391–401. http://dx.doi.org/10.1108/07378831011076648.

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Mohamed, Khaled A., and Ahmed Hassan. "Evaluating Federated Search Tools : A Comparative Study." المجلة الدولية لعلوم المكتبات و المعلومات 1, no. 1 (June 2014): 145–75. http://dx.doi.org/10.12816/0010470.

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Fagan, Jody Condit. "Federated Search Is Dead—and Good Riddance!" Journal of Web Librarianship 5, no. 2 (April 2011): 77–79. http://dx.doi.org/10.1080/19322909.2011.573533.

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Joint, Nicholas. "Managing the implementation of a federated search tool in an academic library." Library Review 58, no. 1 (February 6, 2009): 11–16. http://dx.doi.org/10.1108/00242530910928898.

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PurposeThe purpose of this paper is to look at some of the broader design and management issues that occur during the implementation of a federated search tool in a modern academic library, and tries to tease out some of the background concepts that librarians should consider.Design/methodology/approachAn overview of the main advantages and disadvantages of federated search tools in comparison with existing library tools and internet search engines such as Google.FindingsA successful implementation of a federated search engine was found to depend on a radical approach which subordinates other existing library search tools to the new one‐stop search engine. This new search interface must in turn be designed for simplicity, and not to mimic existing, overly complex library information retrieval devices.Research limitations/implicationsThe emphasis is on the softer, general aspects of managing search tool implementation, rather than the hard, technical side. So, this paper may be best read in tandem with a specific description of a search tool implementation, which describes some of the technical “back office” aspects of federated search. Research developments in these technical areas may well soon lead to the elimination of some of the negative aspects which this paper presents to the non‐technical library manager simply as a “given”.Practical implicationsThis paper outlines many of the practical challenges in search tool implementation which librarians might otherwise not anticipate.Originality/valueThe approach in this investigation is to present the broader implications of search tool implementation in a way that is stripped of technical complexity, in order to show the larger management issues as clearly as possible.

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Belliston, C. Jeffrey, Jared L. Howland, and Brian C. Roberts. "Undergraduate Use of Federated Searching: A Survey of Preferences and Perceptions of Value-added Functionality." College & Research Libraries 68, no. 6 (November 1, 2007): 472–87. http://dx.doi.org/10.5860/crl.68.6.472.

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Randomly selected undergraduates at Brigham Young University, Brigham Young University-Idaho, and Brigham Young University-Hawaii, all private universities sponsored by The Church of Jesus Christ of Latter-day Saints, participated in a study that investigated four questions regarding federated searching: (1) Does it save time? (2) Do undergraduates prefer it? (3) Are undergraduates satisfied with the results they get from it? (4) Does it yield higher-quality results than nonfederated searching? Federated searching was, on average, 11 percent faster than nonfederated searching. Undergraduates rated their satisfaction with the citations gathered by federated searching 17 percent higher than their satisfaction using nonfederated search methods. A majority of undergraduates, 70 percent, preferred federated searching to the alternative. This study could not ultimately determine which of the two search methods yielded higher citation quality. The study does shed light on assumptions about federated searching and will interest librarians in different types of academic institutions, given the diversity of the three institutions studied.

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Yanofsky, Deena. "Students are Confident Using Federated Search Tools as much as Single Databases." Evidence Based Library and Information Practice 6, no. 3 (September 14, 2011): 53. http://dx.doi.org/10.18438/b8sw5r.

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Objective – To measure students’ perceptions of the ease-of-use and efficacy of a federated search tool versus a single multidisciplinary database. Design – An evaluation worksheet, employing a combination of quantitative and qualitative questions. Setting – A required, first-year English composition course taught at the University of Illinois at Chicago (UIC). Subjects – Thirty-one undergraduate students completed and submitted the worksheet. Methods – Students attended two library instruction sessions. The first session introduced participants to basic Boolean searching (using AND only), selecting appropriate keywords and searching for books in the library catalogue. In the second library session, students were handed an evaluation worksheet and, with no introduction to the process of searching article databases, were asked to find relevant articles on a research topic of their own choosing using both a federated search tool and a single multidisciplinary database. The evaluation worksheet was divided into four sections: step-by-step instructions for accessing the single multidisciplinary database and the federated search tool; space to record search strings in both resources; space to record the titles of up to five relevant articles; and a series of quantitative and qualitative questions regarding ease-of-use, relevancy of results, overall preference (if any) between the two resources, likeliness of future use and other preferred research tools. Half of the participants received a worksheet with instructions to search the federated search tool before the single database; the order was reversed for the other half of the students. The evaluation worksheet was designed to be completed in one hour. Participant responses to qualitative questions were analyzed, codified and grouped into thematic categories. If a student mentioned more than one factor in responding to a question, their response was recorded in multiple categories. Main Results – Participants indicated a slight preference for using a federated search tool over a single multidisciplinary database. Of the 31 students who completed the evaluation worksheet, 16 (51.6%) found that their search results were more relevant in the federated search tool; 10 (32.3%) students reported that the articles they found were more relevant in the single database. Three students stated that both search tools produced equally relevant results and two students responded that neither resource produced relevant results on their topic. When asked to state which resource they would be likely to use in the future, 22 students (71%) indicated that they would use the federated search tool and 21 (67.7%) students answered that they would use the single multidisciplinary database. Of the participants who expressed potential use of the single database to look for articles in the future, 43% referred to the ease of use or efficiency of the search tool in their responses. Similarly, more than half of the students who stated that they would use the federated search tool in the future (54.5%) also cited ease of use or efficiency in their answers. In total, 11 students (35.5%) stated that they would be unlikely to use the federated search tool for future research. In their responses, students referred to the inefficiency or complexity of the research tool. Of the 12 participants (38.7%) who stated that they would be unlikely to use the single multidisciplinary database, 50% cited a lack of relevant results and 42% referred to the overall complexity and inefficiency of the database. Conclusions – The results of this study do not support a significant preference among undergraduate students for either search tool. Though some participants struggled with terminology or various features of each resource, more students expressed confidence and satisfaction with the search process no matter which tool they opted to use. Given student confidence and comfort level in both research environments, the author suggests that librarians should place equal weight on both types of resources in library instruction.

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Stafford, Daniel, and Robert Flatley. "Mason OER Metafinder." Charleston Advisor 21, no. 4 (April 1, 2020): 36–39. http://dx.doi.org/10.5260/chara.21.4.36.

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The Mason OER Metafinder (MOM) is a federated search tool created by George Mason University Libraries that searches Open Educational Resources (OER) repositories. The tool features an interface that searches 21 resources including major OER sites like OpenStax and digital repositories like Digital Public Library of America. The reviewers noted several issues with the tool and search results including ambiguous search terms and facets, confusion with the date functionality and search results that included copyrighted materials.

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Theobald, Matthew, Richard Sullivan, and Paul Thompson. "Internet Search Environment Number System: Search infrastructure for a federated environment." Procedia - Social and Behavioral Sciences 26 (2011): 159–65. http://dx.doi.org/10.1016/j.sbspro.2011.10.572.

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Prieto, Joel Manuel. "Psychological state of runners. Differences between federated and non-federated." Revista Guillermo de Ockham 16, no. 1 (June 13, 2018): 45–51. http://dx.doi.org/10.21500/22563202.3845.

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The purpose of this study is to meet the motivations and psychological state of the popular runners, differentiating between federated and non-federated, and between men and women. The sample was composed of 473 popular runners, using Motivations of Marathoners Scales (MOMS) and CSAI-2R to evaluate motivation and anxiety. The results indicate that federated runners present higher scores in sense of life and lower scores in self-confidence, achievement of personal goal, self-esteem and recognition search. On the other hand, the men obtained significantly higher scores on physical fitness, social interaction and attraction to the competition, convenience and competition and lower scores on the meaning of life.

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Koutsomitropoulos, Dimitrios, Georgia Solomou, and Katerina Kalou. "Federated semantic search using terminological thesauri for learning object discovery." Journal of Enterprise Information Management 30, no. 5 (September 11, 2017): 795–808. http://dx.doi.org/10.1108/jeim-06-2016-0116.

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Purpose The purpose of this paper is to propose a framework and system to address the inability to discover new and authentic learning material and the lack of a single access point for search and browsing of remote learning object repositories (LORs). Design/methodology/approach The authors develop a framework for keyword-based query expansion using SKOS domain terminologies and implement a federated search mechanism integrating various disparate LORs within a learning management system (LMS). Findings The authors show that the expanded query achieves improved information gain and it is applied for federated information access, by simultaneously searching within a number of repositories. Results can be seamlessly aggregated back within the LMS and the course context. Practical implications It is possible to retrieve additional learning objects (LOs) and achieve a corresponding increase in recall, while maintaining precision. SKOS expansion behaves well in a scholarly setting, which, combined with federated search, can contribute toward LOs’ discovery at a balanced cost. The system can be easily integrated with other platforms as well, building on open standards and RESTful communication. Originality/value To the authors’ knowledge, this is the first time SKOS-based query expansion is applied in a federated setting, and for the discovery and alignment of learning objects residing within LORs. The results show that this approach can achieve considerable information gain and that it is possible to strike a balance between search effectiveness, query drift and performance.

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Lederman, Abe, Walter Warnick, Brian Hitson, and Lorrie Johnson. "Breaking down language barriers through multilingual federated search." Information Services & Use 30, no. 3-4 (March 3, 2011): 125–32. http://dx.doi.org/10.3233/isu-2010-0617.

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Fillmann Barcelos, Carla, João Carlos Gluz, and Rosa Maria Vicari. "An Agent-based Federated Learning Object Search Service." Interdisciplinary Journal of e-Skills and Lifelong Learning 7 (2011): 037–54. http://dx.doi.org/10.28945/1355.

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Salampasis, Michail, and Allan Hanbury. "PerFedPat: An integrated federated system for patent search." World Patent Information 38 (September 2014): 4–11. http://dx.doi.org/10.1016/j.wpi.2014.08.001.

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George, Carole A. "Lessons learned: usability testing a federated search product." Electronic Library 26, no. 1 (February 15, 2008): 5–20. http://dx.doi.org/10.1108/02640470810851707.

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Taylor, Mary. "Using the Google Search Appliance for Federated Searching." Internet Reference Services Quarterly 10, no. 3-4 (August 27, 2005): 45–55. http://dx.doi.org/10.1300/j136v10n03_06.

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Mohamed, Khaled A., and Ahmed Hassan. "Evaluating federated search tools: usability and retrievability framework." Electronic Library 33, no. 6 (November 2, 2015): 1079–99. http://dx.doi.org/10.1108/el-12-2013-0211.

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Zhu, Yongqing, Quanqing Xu, Haixiang Shi, and Juniarto Samsudin. "An efficient distributed search solution for federated cloud." Distributed and Parallel Databases 35, no. 3-4 (September 11, 2017): 411–33. http://dx.doi.org/10.1007/s10619-017-7201-5.

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Martin, Rob. "Integrated Search Strategies for the Modern Law Firm." Legal Information Management 7, no. 4 (December 2007): 263–68. http://dx.doi.org/10.1017/s1472669607002083.

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AbstractThis article by Rob Martin addresses the issue of effectively managing the searching of enterprise information systems in law firms. It discusses the relative merits of federated, enterprise and integrated search and includes a case study of the combined solution adopted by City law firm, Ashurst.

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Bogstad, Janice M. "Federated Search: Solution or Setback for Online Library Services." Library Collections, Acquisitions, and Technical Services 34, no. 1 (March 2010): 43. http://dx.doi.org/10.1016/j.lcats.2009.08.002.

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Avrahami, Thi Truong, Lawrence Yau, Luo Si, and Jamie Callan. "The FedLemur project: Federated search in the real world." Journal of the American Society for Information Science and Technology 57, no. 3 (2006): 347–58. http://dx.doi.org/10.1002/asi.20283.

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Joint, Nicholas. "Federated search engines and the development of library systems." Library Review 57, no. 9 (October 10, 2008): 653–59. http://dx.doi.org/10.1108/00242530810911770.

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Lampert, Lynn D., and Katherine S. Dabbour. "Librarian Perspectives on Teaching Metasearch and Federated Search Technologies." Internet Reference Services Quarterly 12, no. 3-4 (September 20, 2007): 253–78. http://dx.doi.org/10.1300/j136v12n03_02.

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Bogstad, Janice M. "Federated Search: Solution or Setback for Online Library Services." Library Collections, Acquisitions, & Technical Services 34, no. 1 (January 2010): 43. http://dx.doi.org/10.1080/14649055.2010.10766257.

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Xu, Fei. "Implementation of a Federated Search System: Resource Accessibility Issues." Serials Review 35, no. 4 (December 2009): 235–41. http://dx.doi.org/10.1080/00987913.2009.10765251.

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Garba, Adamu, Shah Khalid, Irfan Ullah, Shah Khusro, and Diyawu Mumin. "Embedding based learning for collection selection in federated search." Data Technologies and Applications 54, no. 5 (October 28, 2020): 703–17. http://dx.doi.org/10.1108/dta-01-2019-0005.

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PurposeThere have been many challenges in crawling deep web by search engines due to their proprietary nature or dynamic content. Distributed Information Retrieval (DIR) tries to solve these problems by providing a unified searchable interface to these databases. Since a DIR must search across many databases, selecting a specific database to search against the user query is challenging. The challenge can be solved if the past queries of the users are considered in selecting collections to search in combination with word embedding techniques. Combining these would aid the best performing collection selection method to speed up retrieval performance of DIR solutions.Design/methodology/approachThe authors propose a collection selection model based on word embedding using Word2Vec approach that learns the similarity between the current and past queries. They used the cosine and transformed cosine similarity models in computing the similarities among queries. The experiment is conducted using three standard TREC testbeds created for federated search.FindingsThe results show significant improvements over the baseline models.Originality/valueAlthough the lexical matching models for collection selection using similarity based on past queries exist, to the best our knowledge, the proposed work is the first of its kind that uses word embedding for collection selection by learning from past queries.

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Lu, Jie. "Full-text federated search in peer-to-peer networks." ACM SIGIR Forum 41, no. 1 (June 2007): 121. http://dx.doi.org/10.1145/1273221.1273233.

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Baillie, Mark, Mark Carman, and Fabio Crestani. "A multi-collection latent topic model for federated search." Information Retrieval 14, no. 4 (October 7, 2010): 390–412. http://dx.doi.org/10.1007/s10791-010-9147-3.

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Ghansah, Benjamin, and Shengli Wu. "A Mean-Variance Analysis Based Approach for Search Result Diversification in Federated Search." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 02 (April 2016): 195–211. http://dx.doi.org/10.1142/s0218488516500100.

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Resource Selection is an important step in a federated search environment. The goal of this work was to improve the collection selection process by selecting collections in terms of relevance and diversity, to best answer a user's query. Sampled documents from the Central Sample Database are first ranked by Indri retrieval algorithm and later re-ranked by a Mean-Standard deviation method that reduces uncertainty and improves diversity of collection sources. A comparative evaluation with the R-based diversification metrics shows that the proposed method significantly outperforms the baseline diversification methods; ReDDE+MMR, ReDDE+MAP-IA and state-of-the-art resource selection methods (ReDDE and CORI) in all metrics.

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Dougan, Kirstin. "The “Black Box”: How Students Use a Single Search Box to Search for Music Materials." Information Technology and Libraries 37, no. 4 (December 17, 2018): 81–106. http://dx.doi.org/10.6017/ital.v37i4.10702.

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Given the inherent challenges music materials present to systems and searchers (formats, title forms and languages, and the presence of additional metadata such as work numbers and keys), it is reasonable that those searching for music develop distinctive search habits compared to patrons in other subject areas. This study uses transaction log analysis of the music and performing arts module of a library’s federated discovery tool to determine how patrons search for music materials. It also makes a top-level comparison of searches done using other broadly defined subject disciplines’ modules in the same discovery tool. It seeks to determine, to the extent possible, whether users in each group have different search behaviors in this search environment. The study also looks more closely at searches in the music module to identify other search characteristics such as type of search conducted, use of advanced search techniques, and any other patterns of search behavior.

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Cooke, Rachel, and Rebecca Donlan. "Thinking Inside the Box: Comparing Federated Search Results from Google Scholar, Live Search Academic, and Central Search." Journal of Library Administration 46, no. 3-4 (March 6, 2008): 31–42. http://dx.doi.org/10.1300/j111v46n03_03.

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Williams, Sarah C., Angela Bonnell, and Bruce Stoffel. "Student Feedback on Federated Search Use, Satisfaction, and Web Presence." Reference & User Services Quarterly 49, no. 2 (December 1, 2009): 131–39. http://dx.doi.org/10.5860/rusq.49n2.131.

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Fatima Warraich, Nosheen, Kanwal Ameen, and Muzammil Tahira. "Usability study of a federated search product at Punjab University." Library Hi Tech News 26, no. 9 (October 23, 2009): 14–15. http://dx.doi.org/10.1108/07419050911010750.

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Wang, Yongming, and Jia Mi. "Searchability and Discoverability of Library Resources: Federated Search and Beyond." College & Undergraduate Libraries 19, no. 2-4 (April 2012): 229–45. http://dx.doi.org/10.1080/10691316.2012.698944.

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Alling, Emily, and Rachael Naismith. "Protocol Analysis of a Federated Search Tool: Designing for Users." Internet Reference Services Quarterly 12, no. 1-2 (September 2007): 195–210. http://dx.doi.org/10.1300/j136v12n01_10.

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Cheung, Kwok, Jane Hunter, and John Drennan. "MatSeek: An Ontology-Based Federated Search Interface for Materials Scientists." IEEE Intelligent Systems 24, no. 1 (January 2009): 47–56. http://dx.doi.org/10.1109/mis.2009.13.

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O'Riordan, Adrian. "Open Search Environments: The Free Alternative to Commercial Search Services." Information Technology and Libraries 33, no. 2 (June 22, 2014): 45. http://dx.doi.org/10.6017/ital.v33i2.4520.

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<em>Open search systems present a free and less restricted alternative to commercial search services. This paper explores the space of open search technology looking in particular at the issue of interoperability. A description of current protocols and formats for engineering open search applications is presented. The suitability of these technologies and issues around their adoption and operation are discussed. This open search approach is especially proving a fitting choice in applications involving the harvesting of resources and information integration. Principal among the technological solutions are OpenSearch and SRU. OpenSearch and SRU implement a federated model to enable existing and new search engines and search clients communicate. Applications and instances where Opensearch and SRU can be combined are presented. Other relevant technologies such as OpenURL, Apache Solr, and OAI-PMH are also discussed. The deployment of these freely licensed open standards in digital library applications is now a genuine alternative to commercial or proprietary systems.</em>

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Coiera, Enrico, Martin Walther, Ken Nguyen, and Nigel H. Lovell. "Architecture for Knowledge-Based and Federated Search of Online Clinical Evidence." Journal of Medical Internet Research 7, no. 5 (October 24, 2005): e52. http://dx.doi.org/10.2196/jmir.7.5.e52.

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Journal articles on the topic 'Federated search'

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