-
Tomaiuolo, N.G.; Parker, J.: Maximizing relevant retrieval : keyword and natural language searching (1998)
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- Source
- Online. 22(1998) no.6, S.57-58
-
Hiemstra, D.; Kraaij, W.: ¬A language-modeling approach to TREC (2005)
0.03
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- Date
- 29. 3.1996 18:16:49
-
¬The Fifth Text Retrieval Conference (TREC-5) (1997)
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- Abstract
- Proceedings of the 5th TREC-confrerence held in Gaithersburgh, Maryland, Nov 20-22, 1996. Aim of the conference was discussion on retrieval techniques for large test collections. Different research groups used different techniques, such as automated thesauri, term weighting, natural language techniques, relevance feedback and advanced pattern matching, for information retrieval from the same large database. This procedure makes it possible to compare the results. The proceedings include papers, tables of the system results, and brief system descriptions including timing and storage information
-
¬The Eleventh Text Retrieval Conference, TREC 2002 (2003)
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- Abstract
- Proceedings of the llth TREC-conference held in Gaithersburg, Maryland (USA), November 19-22, 2002. Aim of the conference was discussion an retrieval and related information-seeking tasks for large test collection. 93 research groups used different techniques, for information retrieval from the same large database. This procedure makes it possible to compare the results. The tasks are: Cross-language searching, filtering, interactive searching, searching for novelty, question answering, searching for video shots, and Web searching.
-
Rijsbergen, C.J. van: ¬A test for the separation of relevant and non-relevant documents in experimental retrieval collections (1973)
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- Date
- 19. 3.1996 11:22:12
- Source
- Journal of documentation. 29(1973) no.3, S.251-257
-
Petrelli, D.: On the role of user-centred evaluation in the advancement of interactive information retrieval (2008)
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- Abstract
- This paper discusses the role of user-centred evaluations as an essential method for researching interactive information retrieval. It draws mainly on the work carried out during the Clarity Project where different user-centred evaluations were run during the lifecycle of a cross-language information retrieval system. The iterative testing was not only instrumental to the development of a usable system, but it enhanced our knowledge of the potential, impact, and actual use of cross-language information retrieval technology. Indeed the role of the user evaluation was dual: by testing a specific prototype it was possible to gain a micro-view and assess the effectiveness of each component of the complex system; by cumulating the result of all the evaluations (in total 43 people were involved) it was possible to build a macro-view of how cross-language retrieval would impact on users and their tasks. By showing the richness of results that can be acquired, this paper aims at stimulating researchers into considering user-centred evaluations as a flexible, adaptable and comprehensive technique for investigating non-traditional information access systems.
- Source
- Information processing and management. 44(2008) no.1, S.22-38
-
Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983)
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- Abstract
- A study was done to test the effectiveness of retrieval using title word searching. It was based on actual search profiles used in the Mechanized Information Center at Ohio State University, in order ro replicate as closely as possible actual searching conditions. Fewer than 50% of the relevant titles were retrieved by keywords in titles. The low rate of retrieval can be attributes to three sources: titles themselves, user and information specialist ignorance of the subject vocabulary in use, and to general language problems. Across fields it was found that the social sciences had the best retrieval rate, with science having the next best, and arts and humanities the lowest. Ways to enhance and supplement keyword in title searching on the computer and in printed indexes are discussed.
- Date
- 14. 3.1996 13:22:21
-
Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002)
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- Abstract
- Answering open-domain factual questions requires Natural Language processing for refining document selection and answer identification. With our system QALC, we have participated in the Question Answering track of the TREC8, TREC9 and TREC10 evaluations. QALC performs an analysis of documents relying an multiword term searches and their linguistic variation both to minimize the number of documents selected and to provide additional clues when comparing question and sentence representations. This comparison process also makes use of the results of a syntactic parsing of the questions and Named Entity recognition functionalities. Answer extraction relies an the application of syntactic patterns chosen according to the kind of information that is sought, and categorized depending an the syntactic form of the question. These patterns allow QALC to handle nicely linguistic variations at the answer level.
- Source
- Knowledge organization. 29(2002) nos.3/4, S.135-155
-
Sievert, M.E.; McKinin, E.J.: Why full-text misses some relevant documents : an analysis of documents not retrieved by CCML or MEDIS (1989)
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- Abstract
- Searches conducted as part of the MEDLINE/Full-Text Research Project revealed that the full-text data bases of clinical medical journal articles (CCML (Comprehensive Core Medical Library) from BRS Information Technologies, and MEDIS from Mead Data Central) did not retrieve all the relevant citations. An analysis of the data indicated that 204 relevant citations were retrieved only by MEDLINE. A comparison of the strategies used on the full-text data bases with the text of the articles of these 204 citations revealed that 2 reasons contributed to these failure. The searcher often constructed a restrictive strategy which resulted in the loss of relevant documents; and as in other kinds of retrieval, the problems of natural language caused the loss of relevant documents.
- Date
- 9. 1.1996 10:22:31
-
Airio, E.: Who benefits from CLIR in web retrieval? (2008)
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- Abstract
- Purpose - The aim of the current paper is to test whether query translation is beneficial in web retrieval. Design/methodology/approach - The language pairs were Finnish-Swedish, English-German and Finnish-French. A total of 12-18 participants were recruited for each language pair. Each participant performed four retrieval tasks. The author's aim was to compare the performance of the translated queries with that of the target language queries. Thus, the author asked participants to formulate a source language query and a target language query for each task. The source language queries were translated into the target language utilizing a dictionary-based system. In English-German, also machine translation was utilized. The author used Google as the search engine. Findings - The results differed depending on the language pair. The author concluded that the dictionary coverage had an effect on the results. On average, the results of query-translation were better than in the traditional laboratory tests. Originality/value - This research shows that query translation in web is beneficial especially for users with moderate and non-active language skills. This is valuable information for developers of cross-language information retrieval systems.
-
Davis, M.W.: On the effective use of large parallel corpora in cross-language text retrieval (1998)
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- Source
- Cross-language information retrieval. Ed.: G. Grefenstette
-
Chu, H.: Factors affecting relevance judgment : a report from TREC Legal track (2011)
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- Date
- 12. 7.2011 18:29:22
-
Voorhees, E.M.; Harman, D.K.: ¬The Text REtrieval Conference (2005)
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- Abstract
- Text retrieval technology targets a problem that is all too familiar: finding relevant information in large stores of electronic documents. The problem is an old one, with the first research conference devoted to the subject held in 1958 [11]. Since then the problem has continued to grow as more information is created in electronic form and more people gain electronic access. The advent of the World Wide Web, where anyone can publish so everyone must search, is a graphic illustration of the need for effective retrieval technology. The Text REtrieval Conference (TREC) is a workshop series designed to build the infrastructure necessary for the large-scale evaluation of text retrieval technology, thereby accelerating its transfer into the commercial sector. The series is sponsored by the U.S. National Institute of Standards and Technology (NIST) and the U.S. Department of Defense. At the time of this writing, there have been twelve TREC workshops and preparations for the thirteenth workshop are under way. Participants in the workshops have been drawn from the academic, commercial, and government sectors, and have included representatives from more than twenty different countries. These collective efforts have accomplished a great deal: a variety of large test collections have been built for both traditional ad hoc retrieval and related tasks such as cross-language retrieval, speech retrieval, and question answering; retrieval effectiveness has approximately doubled; and many commercial retrieval systems now contain technology first developed in TREC.
This book chronicles the evolution of retrieval systems over the course of TREC. To be sure, there has already been a wealth of information written about TREC. Each conference has produced a proceedings containing general overviews of the various tasks, papers written by the individual participants, and evaluation results.1 Reports on expanded versions of TREC experiments frequently appear in the wider information retrieval literature. There also have been special issues of journals devoted to particular TRECs [3; 13] and particular TREC tasks [6; 4]. No single volume could hope to be a comprehensive record of all TREC-related research. Instead, this book looks to distill the overabundance of detail into a manageable whole that summarizes the main lessons learned from TREC. The book consists of three main parts. The first part contains introductory and descriptive chapters on TREC's history, the major products of TREC (the test collections), and the retrieval evaluation methodology. Part II includes chapters describing the major TREC ''tracks,'' evaluations of special subtopics such as cross-language retrieval and question answering. Part III contains contributions from research groups that have participated in TREC. The epilogue to the book is written by Karen Sparck Jones, who reflects on the impact TREC has had on the information retrieval field. The structure of this introductory chapter is similar to that of the book as a whole. The chapter begins with a short history of TREC; expanded descriptions of specific aspects of the history are included in subsequent chapters to make those chapters self-contained. Section 1.2 describes TREC's track structure, which has been responsible for the growth of TREC and allows TREC to adapt to changing needs. The final section lists both the major accomplishments of TREC and some remaining challenges.
- Date
- 29. 3.1996 18:16:49
-
Hansen, P.; Karlgren, J.: Effects of foreign language and task scenario on relevance assessment (2005)
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- Abstract
- Purpose - This paper aims to investigate how readers assess relevance of retrieved documents in a foreign language they know well compared with their native language, and whether work-task scenario descriptions have effect on the assessment process. Design/methodology/approach - Queries, test collections, and relevance assessments were used from the 2002 Interactive CLEF. Swedish first-language speakers, fluent in English, were given simulated information-seeking scenarios and presented with retrieval results in both languages. Twenty-eight subjects in four groups were asked to rate the retrieved text documents by relevance. A two-level work-task scenario description framework was developed and applied to facilitate the study of context effects on the assessment process. Findings - Relevance assessment takes longer in a foreign language than in the user first language. The quality of assessments by comparison with pre-assessed results is inferior to those made in the users' first language. Work-task scenario descriptions had an effect on the assessment process, both by measured access time and by self-report by subjects. However, effects on results by traditional relevance ranking were detectable. This may be an argument for extending the traditional IR experimental topical relevance measures to cater for context effects. Originality/value - An extended two-level work-task scenario description framework was developed and applied. Contextual aspects had an effect on the relevance assessment process. English texts took longer to assess than Swedish and were assessed less well, especially for the most difficult queries. The IR research field needs to close this gap and to design information access systems with users' language competence in mind.
-
Bernstein, L.M.; Williamson, R.E.: Testing of a natural language retrieval system for a full text knowledge base (1984)
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-
Hersh, W.R.; Hickam, D.H.: ¬An evaluation of interactive Boolean and natural language searching with an online medical textbook (1995)
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- Abstract
- Few studies have compared the interactive use of Boolean and natural language search systems. Studies the use of 3 retrieval systems by senior medical students searching on queries generated by actual physicians in a clinical setting. The searchers were randomized to search on 2 or 3 different retrieval systems: a Boolean system, a word-based natural language system, and a concept-based natural language system. Results showed no statistically significant differences in recall or precision among the 3 systems. Likewise, there is no user preference for any system over the other. The study revealed problems with traditional measures of retrieval evaluation when applied to the interactive search setting
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Feldman, S.: Testing natural language : comparing DIALOG, TARGET, and DR-LINK (1996)
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- Abstract
- Compares online searching of DIALOG (a traditional Boolean system), TARGET (a relevance ranking system) and DR-LINK (an advanced intelligent text processing system), in order to establish the differing strengths of traditional and natural language processing search systems. Details example search queries used in comparison and how each of the systems performed. Considers the implications of the findings for professional information searchers and end users. Natural language processing systems are useful because they develop an wider understanding of queries that use of traditional systems may not
-
Bhattacharyya, K.: ¬The effectiveness of natural language in science indexing and retrieval (1974)
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- Abstract
- This paper examines the implications of the findings of evaluative tests regarding the retrieval performance of natural language in various subject fields. It suggests parallel investigations into the structure of natural language, with particular reference to terminology, as used in the different branches of basic science. The criteria for defining the terminological consistency of a subject are formulated and a measure suggested for determining the degree of terminological consistency. The terminological and information structures of specific disciplines such as, chemistry, physics, botany, zoology, and geology; the circumstances in which terms originate; and the efforts made by the international scientific community to standardize the terminology in their respective disciplines - are examined in detail. This investigation shows why and how an artificially created scientific language finds it impossible to keep pace with current developments and thus points to the source of strength of natural language
-
Hofstede, M.: Literatuur over onderwerpen zoeken in de OPC (1994)
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- Source
- CRI bulletin. 29(1994), Sept., S.14-15
-
TREC: experiment and evaluation in information retrieval (2005)
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- Abstract
- The Text REtrieval Conference (TREC), a yearly workshop hosted by the US government's National Institute of Standards and Technology, provides the infrastructure necessary for large-scale evaluation of text retrieval methodologies. With the goal of accelerating research in this area, TREC created the first large test collections of full-text documents and standardized retrieval evaluation. The impact has been significant; since TREC's beginning in 1992, retrieval effectiveness has approximately doubled. TREC has built a variety of large test collections, including collections for such specialized retrieval tasks as cross-language retrieval and retrieval of speech. Moreover, TREC has accelerated the transfer of research ideas into commercial systems, as demonstrated in the number of retrieval techniques developed in TREC that are now used in Web search engines. This book provides a comprehensive review of TREC research, summarizing the variety of TREC results, documenting the best practices in experimental information retrieval, and suggesting areas for further research. The first part of the book describes TREC's history, test collections, and retrieval methodology. Next, the book provides "track" reports -- describing the evaluations of specific tasks, including routing and filtering, interactive retrieval, and retrieving noisy text. The final part of the book offers perspectives on TREC from such participants as Microsoft Research, University of Massachusetts, Cornell University, University of Waterloo, City University of New York, and IBM. The book will be of interest to researchers in information retrieval and related technologies, including natural language processing.
- Content
- Enthält die Beiträge: 1. The Text REtrieval Conference - Ellen M. Voorhees and Donna K. Harman 2. The TREC Test Collections - Donna K. Harman 3. Retrieval System Evaluation - Chris Buckley and Ellen M. Voorhees 4. The TREC Ad Hoc Experiments - Donna K. Harman 5. Routing and Filtering - Stephen Robertson and Jamie Callan 6. The TREC Interactive Tracks: Putting the User into Search - Susan T. Dumais and Nicholas J. Belkin 7. Beyond English - Donna K. Harman 8. Retrieving Noisy Text - Ellen M. Voorhees and John S. Garofolo 9.The Very Large Collection and Web Tracks - David Hawking and Nick Craswell 10. Question Answering in TREC - Ellen M. Voorhees 11. The University of Massachusetts and a Dozen TRECs - James Allan, W. Bruce Croft and Jamie Callan 12. How Okapi Came to TREC - Stephen Robertson 13. The SMART Project at TREC - Chris Buckley 14. Ten Years of Ad Hoc Retrieval at TREC Using PIRCS - Kui-Lam Kwok 15. MultiText Experiments for TREC - Gordon V. Cormack, Charles L. A. Clarke, Christopher R. Palmer and Thomas R. Lynam 16. A Language-Modeling Approach to TREC - Djoerd Hiemstra and Wessel Kraaij 17. BM Research Activities at TREC - Eric W. Brown, David Carmel, Martin Franz, Abraham Ittycheriah, Tapas Kanungo, Yoelle Maarek, J. Scott McCarley, Robert L. Mack, John M. Prager, John R. Smith, Aya Soffer, Jason Y. Zien and Alan D. Marwick Epilogue: Metareflections on TREC - Karen Sparck Jones
- Date
- 29. 3.1996 18:16:49
