Search (128 results, page 1 of 7)

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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.

Imprint

Gaithersburg, MD : National Institute of Standards / Information Technology Laboratory

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Date

11. 8.2001 16:22:19

Source

Information processing and management. 36(2000) no.1, S.3-36

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Abstract

Kekalainen and Jarvelin use what they term generalized, nonbinary recall and precision measures where recall is the sum of the relevance scores of the retrieved documents divided by the sum of relevance scores of all documents in the data base, and precision is the sum of the relevance scores of the retrieved documents divided by the number of documents where the relevance scores are real numbers between zero and one. Using the In-Query system and a text data base of 53,893 newspaper articles with 30 queries selected from those for which four relevance categories to provide recall measures were available, search results were evaluated by four judges. Searches were done by average key term weight, Boolean expression, and by average term weight where the terms are grouped by a synonym operator, and for each case with and without expansion of the original terms. Use of higher standards of relevance appears to increase the superiority of the best method. Some methods do a better job of getting the highly relevant documents but do not increase retrieval of marginal ones. There is evidence that generalized precision provides more equitable results, while binary precision provides undeserved merit to some methods. Generally graded relevance measures seem to provide additional insight into IR evaluation.

Source

Journal of the American Society for Information Science and technology. 53(2002) no.13, S.1120-xxxx

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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.

Footnote

Rez. in: JASIST 58(2007) no.6, S.910-911 (J.L. Vicedo u. J. Gomez): "The Text REtrieval Conference (TREC) is a yearly workshop hosted by the U.S. government's National Institute of Standards and Technology (NIST) that fosters and supports research in information retrieval as well as speeding the transfer of technology between research labs and industry. Since 1992, TREC has provided the infrastructure necessary for large-scale evaluations of different text retrieval methodologies. TREC impact has been very important and its success has been mainly supported by its continuous adaptation to the emerging information retrieval needs. Not in vain, TREC has built evaluation benchmarks for more than 20 different retrieval problems such as Web retrieval, speech retrieval, or question-answering. The large and intense trajectory of annual TREC conferences has resulted in an immense bulk of documents reflecting the different eval uation and research efforts developed. This situation makes it difficult sometimes to observe clearly how research in information retrieval (IR) has evolved over the course of TREC. TREC: Experiment and Evaluation in Information Retrieval succeeds in organizing and condensing all this research into a manageable volume that describes TREC history and summarizes the main lessons learned. The book is organized into three parts. The first part is devoted to the description of TREC's origin and history, the test collections, and the evaluation methodology developed. The second part describes a selection of the major evaluation exercises (tracks), and the third part contains contributions from research groups that had a large and remarkable participation in TREC. Finally, Karen Spark Jones, one of the main promoters of research in IR, closes the book with an epilogue that analyzes the impact of TREC on this research field.
... TREC: Experiment and Evaluation in Information Retrieval is a reliable and comprehensive review of the TREC program and has been adopted by NIST as the official history of TREC (see http://trec.nist.gov). We were favorably surprised by the book. Well structured and written, chapters are self-contained and the existence of references to specialized and more detailed publications is continuous, which makes it easier to expand into the different aspects analyzed in the text. This book succeeds in compiling TREC evolution from its inception in 1992 to 2003 in an adequate and manageable volume. Thanks to the impressive effort performed by the authors and their experience in the field, it can satiate the interests of a great variety of readers. While expert researchers in the IR field and IR-related industrial companies can use it as a reference manual, it seems especially useful for students and non-expert readers willing to approach this research area. Like NIST, we would recommend this reading to anyone who may be interested in textual information retrieval."

LCSH

Information storage and retrieval systems / Congresses

RSWK

Information Retrieval / Textverarbeitung / Aufsatzsammlung (BVB)
Kongress / Information Retrieval / Kongress (GBV)

Subject

Information Retrieval / Textverarbeitung / Aufsatzsammlung (BVB)
Kongress / Information Retrieval / Kongress (GBV)
Information storage and retrieval systems / Congresses

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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.

Source

TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman

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Abstract

A real case study is shown, explaining in a timeline the whole process of design, development and evaluation of a search engine used as a navigational help tool for end users and clients an a content website, e-commerce driven. The nature of the website is a community website, which will determine the core design of the information service. This study will involve several steps, such as information recovery system analysis, comparative analysis of other commercial search engines, service design, functionalities and scope; software selection, design of the project, project management, future service administration and conclusions.

Series

Advances in knowledge organization; vol.8

Source

Challenges in knowledge representation and organization for the 21st century: Integration of knowledge across boundaries. Proceedings of the 7th ISKO International Conference Granada, Spain, July 10-13, 2002. Ed.: M. López-Huertas

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Abstract

Die deutschen Suchmaschinen, Abacho, Acoon, Fireball und Lycos sowie die Web-Kataloge Web.de und Yahoo! werden einem Qualitätstest nach relativem Recall, Precision und Availability unterzogen. Die Methoden der Retrievaltests werden vorgestellt. Im Durchschnitt werden bei einem Cut-Off-Wert von 25 ein Recall von rund 22%, eine Precision von knapp 19% und eine Verfügbarkeit von 24% erreicht

Source

nfd Information - Wissenschaft und Praxis. 52(2001) H.7, S.381-392

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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.

Footnote

Beitrag eines Themenbereichs: Evaluation of Interactive Information Retrieval Systems

Source

Information processing and management. 44(2008) no.1, S.22-38

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Abstract

I had the distinct pleasure of working with Pauline Atherton (Cochrane) during the 1960s, a period that can be considered the heyday of automated information system design and evaluation in the United States. I first met Pauline at the 1962 American Documentation Institute annual meeting in North Hollywood, Florida. My company, Westat Research Analysts, had recently been awarded a contract by the U.S. Patent Office to provide statistical support for the design of experiments with automated information retrieval systems. I was asked to attend the meeting to learn more about information retrieval systems and to begin informing others of U.S. Patent Office activities in this area. At one session, Pauline and I questioned a speaker about the research that he presented. Pauline's questions concerned the logic of their approach and mine, the statistical aspects. After the session, she came over to talk to me and we began a professional and personal friendship that continues to this day. During the 1960s, Pauline was involved in several important information-retrieval projects including a series of studies for the American Institute of Physics, a dissertation examining the relevance of retrieved documents, and development and evaluation of an online information-retrieval system. I had the opportunity to work with Pauline and her colleagues an four of those projects and will briefly describe her work in the 1960s.

Date

22. 9.1997 19:16:05

Imprint

Urbana-Champaign, IL : Illinois University at Urbana-Champaign, Graduate School of Library and Information Science

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Abstract

Relevance judgment has traditionally been considered a personal and subjective matter. A user's search and the search result are treated as an isolated event. To consider the collaborative nature of information retrieval (IR) in a group/organization or even societal context, this article proposes a method that measures relevance based on group/peer consensus. The method can be used in IR experiments. In this method, the relevance of a document is decided by group consensus, or more specifically, by the number of users (or experiment participants) who retrieve it for the same search question. The more users who retrieve it, the more relevant the document will be considered. A user's search performance can be measured by a relevance score based on this notion. The article reports the results of an experiment using this method to compare the search performance of different types of users. Related issues with the method and future directions are also discussed

Source

Journal of the American Society for Information Science and technology. 53(2002) no.3, S.220-231

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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

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Date

9. 2.1997 18:44:22

Source

Journal of librarianship and information science. 32(2000) no.1, S.4-8

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Abstract

This paper reports on a research project that compared two different approaches for the indexing of ordinary images representing common objects: traditional indexing with controlled vocabulary and free indexing with uncontrolled vocabulary. We also compared image retrieval within two contexts: a monolingual context where the language of the query is the same as the indexing language and, secondly, a multilingual context where the language of the query is different from the indexing language. As a means of comparison in evaluating the performance of each indexing form, a simulation of the retrieval process involving 30 images was performed with 60 participants. A questionnaire was also submitted to participants in order to gather information with regard to the retrieval process and performance. The results of the retrieval simulation confirm that the retrieval is more effective and more satisfactory for the searcher when the images are indexed with the approach combining the controlled and uncontrolled vocabularies. The results also indicate that the indexing approach with controlled vocabulary is more efficient (queries needed to retrieve an image) than the uncontrolled vocabulary indexing approach. However, no significant differences in terms of temporal efficiency (time required to retrieve an image) was observed. Finally, the comparison of the two linguistic contexts reveal that the retrieval is more effective and more efficient (queries needed to retrieve an image) in the monolingual context rather than the multilingual context. Furthermore, image searchers are more satisfied when the retrieval is done in a monolingual context rather than a multilingual context.

Source

Knowledge organization. 36(2009) no.4, S.200-213

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Abstract

We report data fusion experiments carried out on the four best-performing retrieval models from TREC 5. Three were conceptually/algorithmically very different from one another; one was algorithmically similar to one of the former. The objective of the test was to observe the performance of the 11 logical data fusion combinations compared to the performance of the four individual models and their intermediate fusions when following the principle of polyrepresentation. This principle is based on cognitive IR perspective (Ingwersen & Järvelin, 2005) and implies that each retrieval model is regarded as a representation of a unique interpretation of information retrieval (IR). It predicts that only fusions of very different, but equally good, IR models may outperform each constituent as well as their intermediate fusions. Two kinds of experiments were carried out. One tested restricted fusions, which entails that only the inner disjoint overlap documents between fused models are ranked. The second set of experiments was based on traditional data fusion methods. The experiments involved the 30 TREC 5 topics that contain more than 44 relevant documents. In all tests, the Borda and CombSUM scoring methods were used. Performance was measured by precision and recall, with document cutoff values (DCVs) at 100 and 15 documents, respectively. Results show that restricted fusions made of two, three, or four cognitively/algorithmically very different retrieval models perform significantly better than do the individual models at DCV100. At DCV15, however, the results of polyrepresentative fusion were less predictable. The traditional fusion method based on polyrepresentation principles demonstrates a clear picture of performance at both DCV levels and verifies the polyrepresentation predictions for data fusion in IR. Data fusion improves retrieval performance over their constituent IR models only if the models all are quite conceptually/algorithmically dissimilar and equally and well performing, in that order of importance.

Date

22. 3.2009 18:48:28

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.646-654

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LCSH

Information storage and retrieval systems / Evaluation

RSWK

Information Retrieval / Datenbankverwaltung / Hochschulschrift (GBV)
Information Retrieval / Dialogsystem (SWB)
Information Retrieval / Dialogsystem / Leistungsbewertung (BVB)

Subject

Information Retrieval / Datenbankverwaltung / Hochschulschrift (GBV)
Information Retrieval / Dialogsystem (SWB)
Information Retrieval / Dialogsystem / Leistungsbewertung (BVB)
Information storage and retrieval systems / Evaluation

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Source

Information processing and management. 37(2001) no.1, S.163-182

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Source

Journal of information science. 29(2003) no.4, S.239-248

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Abstract

Die Menge an Daten im Internet steigt weiter rapide an. Damit wächst auch der Bedarf an qualitativ hochwertigen Information Retrieval Diensten zur Orientierung und problemorientierten Suche. Die Entscheidung für die Benutzung oder Beschaffung von Information Retrieval Software erfordert aussagekräftige Evaluierungsergebnisse. Dieser Beitrag stellt neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen vor und zeigt den Trend zu Spezialisierung und Diversifizierung von Evaluierungsstudien, die den Realitätsgrad derErgebnisse erhöhen. DerSchwerpunkt liegt auf dem Retrieval von Fachtexten, Internet-Seiten und Multimedia-Objekten.

Source

Information - Wissenschaft und Praxis. 54(2003) H.4, S.203-210

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Abstract

This article works towards realization of exosomatic memory for information systems. In exosomatic memory systems, the information spaces of systems will be consistent with the cognitive spaces of their human users. A method for measuring concept relations in human cognitive space is presented: the paired comparison survey with Principal Components Analysis. A study to measure the cognitive spaces of 16 research participants is presented. Items measured include relations among seven TREC topic statements as well as 17 concepts from the topic statements. A method for automatically generating information spaces from document collections is presented that uses term cooccurrence, eigensystems analysis, and Principal Components Analysis. The extent of similarity between the cognitive spaces and the information spaces, which were derived independently from each other, is measured. A strong similarity between the information spaces and the cognitive spaces are found, indicating that the methods described may have good utility for working towards information systems that operate as exosomatic memories

Source

Journal of the American Society for Information Science and technology. 52(2001) no.12, S.1026-1048

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Source

Information Research. 8(2003), no.3