-
Salton, G.: Thoughts about modern retrieval technologies (1988)
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- Abstract
- Paper presented at the 30th Annual Conference of the National Federation of Astracting and Information Services, Philadelphia, 28 Feb-2 Mar 88. In recent years, the amount and the variety of available machine-readable data, new technologies have been introduced, such as high density storage devices, and fancy graphic displays useful for information transformation and access. New approaches have also been considered for processing the stored data based on the construction of knowledge bases representing the contents and structure of the information, and the use of expert system techniques to control the user-system interactions. Provides a brief evaluation of the new information processing technologies, and of the software methods proposed for information manipulation.
-
Losee, R.M.: Determining information retrieval and filtering performance without experimentation (1995)
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- Abstract
- The performance of an information retrieval or text and media filtering system may be determined through analytic methods as well as by traditional simulation or experimental methods. These analytic methods can provide precise statements about expected performance. They can thus determine which of 2 similarly performing systems is superior. For both a single query terms and for a multiple query term retrieval model, a model for comparing the performance of different probabilistic retrieval methods is developed. This method may be used in computing the average search length for a query, given only knowledge of database parameter values. Describes predictive models for inverse document frequency, binary independence, and relevance feedback based retrieval and filtering. Simulation illustrate how the single term model performs and sample performance predictions are given for single term and multiple term problems
- Date
- 22. 2.1996 13:14:10
-
Ng, K.B.; Loewenstern, D.; Basu, C.; Hirsh, H.; Kantor, P.B.: Data fusion of machine-learning methods for the TREC5 routing tak (and other work) (1997)
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- Date
- 27. 2.1999 20:59:22
-
Lespinasse, K.: TREC: une conference pour l'evaluation des systemes de recherche d'information (1997)
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- Abstract
- TREC ia an annual conference held in the USA devoted to electronic systems for large full text information searching. The conference deals with evaluation and comparison techniques developed since 1992 by participants from the research and industrial fields. The work of the conference is destined for designers (rather than users) of systems which access full text information. Describes the context, objectives, organization, evaluation methods and limits of TREC
- Date
- 1. 8.1996 22:01:00
-
Blagden, J.F.: How much noise in a role-free and link-free co-ordinate indexing system? (1966)
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- Abstract
- A study of the number of irrelevant documents retrieved in a co-ordinate indexing system that does not employ eitherr roles or links. These tests were based on one hundred actual inquiries received in the library and therefore an evaluation of recall efficiency is not included. Over half the enquiries produced no noise, but the mean average percentage niose figure was approximately 33 per cent based on a total average retireval figure of eighteen documents per search. Details of the size of the indexed collection, methods of indexing, and an analysis of the reasons for the retrieval of irrelevant documents are discussed, thereby providing information officers who are thinking of installing such a system with some evidence on which to base a decision as to whether or not to utilize these devices
- Source
- Journal of documentation. 22(1966), S.203-209
-
Leininger, K.: Interindexer consistency in PsychINFO (2000)
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- Abstract
- Reports results of a study to examine interindexer consistency (the degree to which indexers, when assigning terms to a chosen record, will choose the same terms to reflect that record) in the PsycINFO database using 60 records that were inadvertently processed twice between 1996 and 1998. Five aspects of interindexer consistency were analysed. Two methods were used to calculate interindexer consistency: one posited by Hooper (1965) and the other by Rollin (1981). Aspects analysed were: checktag consistency (66.24% using Hooper's calculation and 77.17% using Rollin's); major-to-all term consistency (49.31% and 62.59% respectively); overall indexing consistency (49.02% and 63.32%); classification code consistency (44.17% and 45.00%); and major-to-major term consistency (43.24% and 56.09%). The average consistency across all categories was 50.4% using Hooper's method and 60.83% using Rollin's. Although comparison with previous studies is difficult due to methodological variations in the overall study of indexing consistency and the specific characteristics of the database, results generally support previous findings when trends and similar studies are analysed.
- Date
- 9. 2.1997 18:44:22
-
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.
-
Pal, S.; Mitra, M.; Kamps, J.: Evaluation effort, reliability and reusability in XML retrieval (2011)
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- Abstract
- The Initiative for the Evaluation of XML retrieval (INEX) provides a TREC-like platform for evaluating content-oriented XML retrieval systems. Since 2007, INEX has been using a set of precision-recall based metrics for its ad hoc tasks. The authors investigate the reliability and robustness of these focused retrieval measures, and of the INEX pooling method. They explore four specific questions: How reliable are the metrics when assessments are incomplete, or when query sets are small? What is the minimum pool/query-set size that can be used to reliably evaluate systems? Can the INEX collections be used to fairly evaluate "new" systems that did not participate in the pooling process? And, for a fixed amount of assessment effort, would this effort be better spent in thoroughly judging a few queries, or in judging many queries relatively superficially? The authors' findings validate properties of precision-recall-based metrics observed in document retrieval settings. Early precision measures are found to be more error-prone and less stable under incomplete judgments and small topic-set sizes. They also find that system rankings remain largely unaffected even when assessment effort is substantially (but systematically) reduced, and confirm that the INEX collections remain usable when evaluating nonparticipating systems. Finally, they observe that for a fixed amount of effort, judging shallow pools for many queries is better than judging deep pools for a smaller set of queries. However, when judging only a random sample of a pool, it is better to completely judge fewer topics than to partially judge many topics. This result confirms the effectiveness of pooling methods.
- Date
- 22. 1.2011 14:20:56
-
Larsen, B.; Ingwersen, P.; Lund, B.: Data fusion according to the principle of polyrepresentation (2009)
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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
-
Vechtomova, O.: Facet-based opinion retrieval from blogs (2010)
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- Abstract
- The paper presents methods of retrieving blog posts containing opinions about an entity expressed in the query. The methods use a lexicon of subjective words and phrases compiled from manually and automatically developed resources. One of the methods uses the Kullback-Leibler divergence to weight subjective words occurring near query terms in documents, another uses proximity between the occurrences of query terms and subjective words in documents, and the third combines both factors. Methods of structuring queries into facets, facet expansion using Wikipedia, and a facet-based retrieval are also investigated in this work. The methods were evaluated using the TREC 2007 and 2008 Blog track topics, and proved to be highly effective.
-
Losada, D.E.; Parapar, J.; Barreiro, A.: Multi-armed bandits for adjudicating documents in pooling-based evaluation of information retrieval systems (2017)
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- Abstract
- Evaluating Information Retrieval systems is crucial to making progress in search technologies. Evaluation is often based on assembling reference collections consisting of documents, queries and relevance judgments done by humans. In large-scale environments, exhaustively judging relevance becomes infeasible. Instead, only a pool of documents is judged for relevance. By selectively choosing documents from the pool we can optimize the number of judgments required to identify a given number of relevant documents. We argue that this iterative selection process can be naturally modeled as a reinforcement learning problem and propose innovative and formal adjudication methods based on multi-armed bandits. Casting document judging as a multi-armed bandit problem is not only theoretically appealing, but also leads to highly effective adjudication methods. Under this bandit allocation framework, we consider stationary and non-stationary models and propose seven new document adjudication methods (five stationary methods and two non-stationary variants). Our paper also reports a series of experiments performed to thoroughly compare our new methods against current adjudication methods. This comparative study includes existing methods designed for pooling-based evaluation and existing methods designed for metasearch. Our experiments show that our theoretically grounded adjudication methods can substantially minimize the assessment effort.
-
Ekmekcioglu, F.C.; Robertson, A.M.; Willett, P.: Effectiveness of query expansion in ranked-output document retrieval systems (1992)
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- Abstract
- Reports an evaluation of 3 methods for the expansion of natural language queries in ranked output retrieval systems. The methods are based on term co-occurrence data, on Soundex codes, and on a string similarity measure. Searches for 110 queries in a data base of 26.280 titles and abstracts suggest that there is no significant difference in retrieval effectiveness between any of these methods and unexpanded searches
-
Losada, D.E.; Parapar, J.; Barreiro, A.: When to stop making relevance judgments? : a study of stopping methods for building information retrieval test collections (2019)
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- Abstract
- In information retrieval evaluation, pooling is a well-known technique to extract a sample of documents to be assessed for relevance. Given the pooled documents, a number of studies have proposed different prioritization methods to adjudicate documents for judgment. These methods follow different strategies to reduce the assessment effort. However, there is no clear guidance on how many relevance judgments are required for creating a reliable test collection. In this article we investigate and further develop methods to determine when to stop making relevance judgments. We propose a highly diversified set of stopping methods and provide a comprehensive analysis of the usefulness of the resulting test collections. Some of the stopping methods introduced here combine innovative estimates of recall with time series models used in Financial Trading. Experimental results on several representative collections show that some stopping methods can reduce up to 95% of the assessment effort and still produce a robust test collection. We demonstrate that the reduced set of judgments can be reliably employed to compare search systems using disparate effectiveness metrics such as Average Precision, NDCG, P@100, and Rank Biased Precision. With all these measures, the correlations found between full pool rankings and reduced pool rankings is very high.
-
Davis, M.; Dunning, T.: ¬A TREC evaluation of query translation methods for multi-lingual text retrieval (1996)
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-
Pfeifer, U.; Poersch, T.; Fuhr, N.: Retrieval effectiveness of proper name search methods (1996)
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- Abstract
- Reviews similarity measures for searching names. These measures deal with phonetic similarity, typing errors, and plain string similarity. Shows experimentally that all 3 approaches lead to significantly higher retrieval quality than plain identity. Further improvements are possible by combining different methods. Develops a probabilistic interpretation of string similarity that leads to better results than an ad-hoc approach
-
Bar-Ilan, J.: Methods for measuring search engine performance over time (2002)
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- Abstract
- This study introduces methods for evaluating search engine performance over a time period. Several measures are defined, which as a whole describe search engine functionality over time. The necessary setup for such studies is described, and the use of these measures is illustrated through a specific example. The set of measures introduced here may serve as a guideline for the search engines for testing and improving their functionality. We recommend setting up a standard suite of measures for evaluating search engine performance.
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Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984)
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- Date
- 20.10.2000 12:22:23
-
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
-
Voorhees, E.M.; Harman, D.: Overview of the Sixth Text REtrieval Conference (TREC-6) (2000)
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- Date
- 11. 8.2001 16:22:19
-
Dalrymple, P.W.: Retrieval by reformulation in two library catalogs : toward a cognitive model of searching behavior (1990)
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- Date
- 22. 7.2006 18:43:54
