-
Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
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- Date
- 30. 3.2001 13:32:22
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Thompson, P.: Looking back: on relevance, probabilistic indexing and information retrieval (2008)
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- Abstract
- Forty-eight years ago Maron and Kuhns published their paper, "On Relevance, Probabilistic Indexing and Information Retrieval" (1960). This was the first paper to present a probabilistic approach to information retrieval, and perhaps the first paper on ranked retrieval. Although it is one of the most widely cited papers in the field of information retrieval, many researchers today may not be familiar with its influence. This paper describes the Maron and Kuhns article and the influence that it has had on the field of information retrieval.
- Date
- 31. 7.2008 19:58:29
-
Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986)
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- Source
- Information processing and management. 22(1986) no.6, S.465-476
-
Crestani, F.: Combination of similarity measures for effective spoken document retrieval (2003)
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- Source
- Journal of information science. 29(2003) no.2, S.87-96
-
Faloutsos, C.: Signature files (1992)
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- Abstract
- Presents a survey and discussion on signature-based text retrieval methods. It describes the main idea behind the signature approach and its advantages over other text retrieval methods, it provides a classification of the signature methods that have appeared in the literature, it describes the main representatives of each class, together with the relative advantages and drawbacks, and it gives a list of applications as well as commercial or university prototypes that use the signature approach
- Date
- 7. 5.1999 15:22:48
- Source
- Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
-
Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003)
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- Abstract
- We propose a novel approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. The ability of the logic to handle expressive representations along with the use of such classical notions are promising characteristics for IR systems. The approach proposed here has been efficiently implemented and experiments against test collections are presented.
- Date
- 22. 3.2003 19:27:23
- Footnote
- Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
-
Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998)
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- Date
- 11. 8.2001 14:48:29
-
Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003)
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- Abstract
- Research an the use of mathematical, logical, and formal methods, has been central to Information Retrieval research for a long time. Research in this area is important not only because it helps enhancing retrieval effectiveness, but also because it helps clarifying the underlying concepts of Information Retrieval. In this article we outline some of the major aspects of the subject, and summarize the papers of this special issue with respect to how they relate to these aspects. We conclude by highlighting some directions of future research, which are needed to better understand the formal characteristics of Information Retrieval.
- Date
- 22. 3.2003 19:27:36
- Footnote
- Einführung zu den Beiträgen eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
-
Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995)
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- Abstract
- The retrieval effectiveness of 5 hierarchical clustering methods (single link, complete link, group average, Ward's method, and weighted average) is examined as a function of indexing exhaustivity with 4 test collections (CR, Cranfield, Medlars, and Time). Evaluations of retrieval effectiveness, based on 3 measures of optimal retrieval performance, confirm earlier findings that the performance of a retrieval system based on single link clustering varies as a function of indexing exhaustivity but fail ti find similar patterns for other clustering methods. The data also confirm earlier findings regarding the poor performance of single link clustering is a retrieval environment. The poor performance of single link clustering appears to derive from that method's tendency to produce a small number of large, ill defined document clusters. By contrast, the data examined here found the retrieval performance of the other clustering methods to be general comparable. The data presented also provides an opportunity to examine the theoretical limits of cluster based retrieval and to compare these theoretical limits to the effectiveness of operational implementations. Performance standards of the 4 document collections examined were found to vary widely, and the effectiveness of operational implementations were found to be in the range defined as unacceptable. Further improvements in search strategies and document representations warrant investigations
- Date
- 22. 2.1996 11:20:06
-
Archuby, C.G.: Interfaces se recuperacion para catalogos en linea con salidas ordenadas por probable relevancia (2000)
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- Date
- 29. 1.1996 18:23:13
- Footnote
- Übers. d. Titels: Interface for retrieval from online access catalogues with ranked results according to their relevance
- Source
- Ciencia da informacao. 29(2000) no.3, S.5-13
-
Paris, L.A.H.; Tibbo, H.R.: Freestyle vs. Boolean : a comparison of partial and exact match retrieval systems (1998)
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- Abstract
- Compares the performance of partial match options, LEXIS/NEXIS's Freestyle, with that of traditional Boolean retrieval. Defines natural language and the natural language search engines currently available. Although the Boolean searches had better results more often than the Freestyle searches, neither mechanism demonstrated superior performance for every query. These results do not in any way prove the superiority of partial match techniques or exact match techniques, but they do suggest that different queries demand different techniques. Further study and analysis are needed to determine which elements of a query make it best suited for partial match or exact match retrieval
- Date
- 12. 3.1999 10:29:27
-
Otterbacher, J.; Erkan, G.; Radev, D.R.: Biased LexRank : passage retrieval using random walks with question-based priors (2009)
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- Abstract
- We present Biased LexRank, a method for semi-supervised passage retrieval in the context of question answering. We represent a text as a graph of passages linked based on their pairwise lexical similarity. We use traditional passage retrieval techniques to identify passages that are likely to be relevant to a user's natural language question. We then perform a random walk on the lexical similarity graph in order to recursively retrieve additional passages that are similar to other relevant passages. We present results on several benchmarks that show the applicability of our work to question answering and topic-focused text summarization.
- Date
- 22.11.2008 17:11:29
-
Ayadi, H.; Torjmen-Khemakhem, M.; Daoud, M.; Xiangji Huang, J.; Ben Jemaa, M.: MF-Re-Rank : a modality feature-based re-ranking model for medical image retrieval (2018)
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- Abstract
- One of the main challenges in medical image retrieval is the increasing volume of image data, which render it difficult for domain experts to find relevant information from large data sets. Effective and efficient medical image retrieval systems are required to better manage medical image information. Text-based image retrieval (TBIR) was very successful in retrieving images with textual descriptions. Several TBIR approaches rely on models based on bag-of-words approaches, in which the image retrieval problem turns into one of standard text-based information retrieval; where the meanings and values of specific medical entities in the text and metadata are ignored in the image representation and retrieval process. However, we believe that TBIR should extract specific medical entities and terms and then exploit these elements to achieve better image retrieval results. Therefore, we propose a novel reranking method based on medical-image-dependent features. These features are manually selected by a medical expert from imaging modalities and medical terminology. First, we represent queries and images using only medical-image-dependent features such as image modality and image scale. Second, we exploit the defined features in a new reranking method for medical image retrieval. Our motivation is the large influence of image modality in medical image retrieval and its impact on image-relevance scores. To evaluate our approach, we performed a series of experiments on the medical ImageCLEF data sets from 2009 to 2013. The BM25 model, a language model, and an image-relevance feedback model are used as baselines to evaluate our approach. The experimental results show that compared to the BM25 model, the proposed model significantly enhances image retrieval performance. We also compared our approach with other state-of-the-art approaches and show that our approach performs comparably to those of the top three runs in the official ImageCLEF competition.
- Date
- 29. 9.2018 11:43:31
-
MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004)
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- Abstract
- In this paper methods for both speeding up passage processing and examining more passages using parallel computers are explored. The number of passages processed are varied in order to examine the effect on retrieval effectiveness and efficiency. The particular algorithm applied has previously been used to good effect in Okapi experiments at TREC. This algorithm and the mechanism for applying parallel computing to speed up processing are described.
- Date
- 20. 1.2007 18:30:22
-
Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995)
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- Abstract
- Shows how probabilistic information retrieval based on document components may be implemented as a feedforward (feedbackward) artificial neural network. The network supports adaptation of connection weights as well as the growing of new edges between queries and terms based on user relevance feedback data for training, and it reflects query modification and expansion in information retrieval. A learning rule is applied that can also be viewed as supporting sequential learning using a harmonic sequence learning rate. Experimental results with 4 standard small collections and a large Wall Street Journal collection show that small query expansion levels of about 30 terms can achieve most of the gains at the low-recall high-precision region, while larger expansion levels continue to provide gains at the high-recall low-precision region of a precision recall curve
- Date
- 29. 1.1996 18:42:14
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Qi, Q.; Hessen, D.J.; Heijden, P.G.M. van der: Improving information retrieval through correspondenceanalysis instead of latent semantic analysis (2023)
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- Abstract
- The initial dimensions extracted by latent semantic analysis (LSA) of a document-term matrixhave been shown to mainly display marginal effects, which are irrelevant for informationretrieval. To improve the performance of LSA, usually the elements of the raw document-term matrix are weighted and the weighting exponent of singular values can be adjusted.An alternative information retrieval technique that ignores the marginal effects is correspon-dence analysis (CA). In this paper, the information retrieval performance of LSA and CA isempirically compared. Moreover, it is explored whether the two weightings also improve theperformance of CA. The results for four empirical datasets show that CA always performsbetter than LSA. Weighting the elements of the raw data matrix can improve CA; however,it is data dependent and the improvement is small. Adjusting the singular value weightingexponent often improves the performance of CA; however, the extent of the improvementdepends on the dataset and the number of dimensions. (PDF) Improving information retrieval through correspondence analysis instead of latent semantic analysis.
- Date
- 15. 9.2023 12:28:29
-
Witschel, H.F.: Global term weights in distributed environments (2008)
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- Abstract
- This paper examines the estimation of global term weights (such as IDF) in information retrieval scenarios where a global view on the collection is not available. In particular, the two options of either sampling documents or of using a reference corpus independent of the target retrieval collection are compared using standard IR test collections. In addition, the possibility of pruning term lists based on frequency is evaluated. The results show that very good retrieval performance can be reached when just the most frequent terms of a collection - an "extended stop word list" - are known and all terms which are not in that list are treated equally. However, the list cannot always be fully estimated from a general-purpose reference corpus, but some "domain-specific stop words" need to be added. A good solution for achieving this is to mix estimates from small samples of the target retrieval collection with ones derived from a reference corpus.
- Date
- 1. 8.2008 9:44:22
-
Dominich, S.: Mathematical foundations of information retrieval (2001)
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- Abstract
- This book offers a comprehensive and consistent mathematical approach to information retrieval (IR) without which no implementation is possible, and sheds an entirely new light upon the structure of IR models. It contains the descriptions of all IR models in a unified formal style and language, along with examples for each, thus offering a comprehensive overview of them. The book also creates mathematical foundations and a consistent mathematical theory (including all mathematical results achieved so far) of IR as a stand-alone mathematical discipline, which thus can be read and taught independently. Also, the book contains all necessary mathematical knowledge on which IR relies, to help the reader avoid searching different sources. The book will be of interest to computer or information scientists, librarians, mathematicians, undergraduate students and researchers whose work involves information retrieval.
- Date
- 22. 3.2008 12:26:32
- LCSH
- Information storage and retrieval
- Subject
- Information storage and retrieval
-
Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996)
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- Abstract
- Traces the development of text searching and retrieval software designed to cope with the increasing demands made by the storage and handling of large amounts of data, recorded on high data storage media, from CD-ROM to multi gigabyte storage media and online information services, with particular reference to the need to cope with graphics as well as conventional ASCII text. Includes details of: Boolean searching, fuzzy searching and matching; relevance ranking; proximity searching and improved strategies for dealing with text searching in very large databases. Concludes that the best searching tools for CD-ROM publishers are those optimized for searching and retrieval on CD-ROM. CD-ROM drives have relatively lower random seek times than hard discs and so the software most appropriate to the medium is that which can effectively arrange the indexes and text on the CD-ROM to avoid continuous random access searching. Lists and reviews a selection of software packages designed to achieve the sort of results required for rapid CD-ROM searching
- Date
- 12. 9.1996 13:56:22
-
Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003)
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- Abstract
- Relevance Feedback consists in automatically formulating a new query according to the relevance judgments provided by the user after evaluating a set of retrieved documents. In this article, we introduce several relevance feedback methods for the Bayesian Network Retrieval ModeL The theoretical frame an which our methods are based uses the concept of partial evidences, which summarize the new pieces of information gathered after evaluating the results obtained by the original query. These partial evidences are inserted into the underlying Bayesian network and a new inference process (probabilities propagation) is run to compute the posterior relevance probabilities of the documents in the collection given the new query. The quality of the proposed methods is tested using a preliminary experimentation with different standard document collections.
- Date
- 22. 3.2003 19:30:19
- Footnote
- Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
