-
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
-
Hofferer, M.: Heuristic search in information retrieval (1994)
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- Abstract
- Describes an adaptive information retrieval system: Information Retrieval Algorithm System (IRAS); that uses heuristic searching to sample a document space and retrieve relevant documents according to users' requests; and also a learning module based on a knowledge representation system and an approximate probabilistic characterization of relevant documents; to reproduce a user classification of relevant documents and to provide a rule controlled ranking
- Source
- Information retrieval: new systems and current research. Proceedings of the 15th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Glasgow 1993. Ed.: Ruben Leon
-
Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004)
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- Abstract
- The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
- Date
- 16.11.2008 16:22:48
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Beitzel, S.M.; Jensen, E.C.; Chowdhury, A.; Grossman, D.; Frieder, O; Goharian, N.: Fusion of effective retrieval strategies in the same information retrieval system (2004)
0.02
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- Abstract
- Prior efforts have shown that under certain situations retrieval effectiveness may be improved via the use of data fusion techniques. Although these improvements have been observed from the fusion of result sets from several distinct information retrieval systems, it has often been thought that fusing different document retrieval strategies in a single information retrieval system will lead to similar improvements. In this study, we show that this is not the case. We hold constant systemic differences such as parsing, stemming, phrase processing, and relevance feedback, and fuse result sets generated from highly effective retrieval strategies in the same information retrieval system. From this, we show that data fusion of highly effective retrieval strategies alone shows little or no improvement in retrieval effectiveness. Furthermore, we present a detailed analysis of the performance of modern data fusion approaches, and demonstrate the reasons why they do not perform weIl when applied to this problem. Detailed results and analyses are included to support our conclusions.
- Source
- Journal of the American Society for Information Science and Technology. 55(2004) no.10, S.859-868
-
Frants, V.I.; Shapiro, J.: Control and feedback in a documentary information retrieval system (1991)
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- Abstract
- Addresses the problem of control in documentary information retrieval systems is analysed and it is shown why an IR system has to be looked at as an adaptive system. The algorithms of feedback are proposed and it is shown how they depend on the type of the collection of documents: static (no change in the collection between searches) and dynamic (when the change occurs between searches). The proposed algorithms are the basis for the development of the fully automated information retrieval systems
- Source
- Journal of the American Society for Information Science. 42(1991) no.9, S.623-634
-
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
- Source
- Journal of the American Society for Information Science. 46(1995) no.8, S.562-572
-
Zhu, B.; Chen, H.: Validating a geographical image retrieval system (2000)
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- Abstract
- This paper summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. By using an image as its interface, the prototype system addresses a troublesome aspect of traditional retrieval models, which require users to have complete knowledge of the low-level features of an image. In addition we describe an experiment to validate against that of human subjects in an effort to address the scarcity of research evaluating performance of an algorithm against that of human beings. The results of the experiment indicate that the system could do as well as human subjects in accomplishing the tasks of similarity analysis and image categorization. We also found that under some circumstances texture features of an image are insufficient to represent an geographic image. We believe, however, that our image retrieval system provides a promising approach to integrating image processing techniques and information retrieval algorithms
- Source
- Journal of the American Society for Information Science. 51(2000) no.7, S.625-634
-
Beaulieu, M.; Jones, S.: Interactive searching and interface issues in the Okapi best match probabilistic retrieval system (1998)
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- Abstract
- Explores interface design raised by the development and evaluation of Okapi, a highly interactive information retrieval system based on a probabilistic retrieval model with relevance feedback. It uses terms frequency weighting functions to display retrieved items in a best match ranked order; it can also find additional items similar to those marked as relevant by the searcher. Compares the effectiveness of automatic and interactive query expansion in different user interface environments. focuses on the nature of interaction in information retrieval and the interrelationship between functional visibility, the user's cognitive loading and the balance of control between user and system
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
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
-
Carpineto, C.; Romano, G.: Information retrieval through hybrid navigation of lattice representations (1996)
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- Abstract
- Presents a comprehensive approach to automatic organization and hybrid navigation of text databases. An organizing stage builds a particular lattice representation of the data, through text indexing followed by lattice clustering of the indexed texts. The lattice representation supports the navigation state of the system, a visual retrieval interface that combines 3 main retrieval strategies: browsing, querying, and bounding. Such a hybrid paradigm permits high flexibility in trading off information exploration and retrieval, and had good retrieval performance. Compares information retrieval using lattice-based hybrid navigation with conventional Boolean querying. Experiments conducted on 2 medium-sized bibliographic databases showed that the performance of lattice retrieval was comparable to or better than Boolean retrieval
-
Ravana, S.D.; Rajagopal, P.; Balakrishnan, V.: Ranking retrieval systems using pseudo relevance judgments (2015)
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- Abstract
- Purpose In a system-based approach, replicating the web would require large test collections, and judging the relevancy of all documents per topic in creating relevance judgment through human assessors is infeasible. Due to the large amount of documents that requires judgment, there are possible errors introduced by human assessors because of disagreements. The paper aims to discuss these issues. Design/methodology/approach This study explores exponential variation and document ranking methods that generate a reliable set of relevance judgments (pseudo relevance judgments) to reduce human efforts. These methods overcome problems with large amounts of documents for judgment while avoiding human disagreement errors during the judgment process. This study utilizes two key factors: number of occurrences of each document per topic from all the system runs; and document rankings to generate the alternate methods. Findings The effectiveness of the proposed method is evaluated using the correlation coefficient of ranked systems using mean average precision scores between the original Text REtrieval Conference (TREC) relevance judgments and pseudo relevance judgments. The results suggest that the proposed document ranking method with a pool depth of 100 could be a reliable alternative to reduce human effort and disagreement errors involved in generating TREC-like relevance judgments. Originality/value Simple methods proposed in this study show improvement in the correlation coefficient in generating alternate relevance judgment without human assessors while contributing to information retrieval evaluation.
- Date
- 20. 1.2015 18:30:22
18. 9.2018 18:22:56
- Source
- Aslib journal of information management. 67(2015) no.6, S.700-714
-
Harman, D.: Ranking algorithms (1992)
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- Abstract
- Presents both a summary of past research done in the development of ranking algorithms and detailed instructions on implementing a ranking type of retrieval system. This type of retrieval system takes as input a natural language query without Boolean syntax and produces a list of records that 'answer' the query, with the records ranked in order of likely relevance. Ranking retrieval systems are particularly appropriate for end-users
- Source
- Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
-
Rajashekar, T.B.; Croft, W.B.: Combining automatic and manual index representations in probabilistic retrieval (1995)
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- Abstract
- Results from research in information retrieval have suggested that significant improvements in retrieval effectiveness can be obtained by combining results from multiple index representioms, query formulations, and search strategies. The inference net model of retrieval, which was designed from this point of view, treats information retrieval as an evidental reasoning process where multiple sources of evidence about document and query content are combined to estimate relevance probabilities. Uses a system based on this model to study the retrieval effectiveness benefits of combining these types of document and query information that are found in typical commercial databases and information services. The results indicate that substantial real benefits are possible
- Source
- Journal of the American Society for Information Science. 46(1995) no.4, S.272-283
-
Wilbur, W.J.: ¬A retrieval system based on automatic relevance weighting of search terms (1992)
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- Abstract
- Describes the development of a retrieval system based on automatic relevance weighting of search terms and founded on the Bayesian formulation of the probability of relevance as function of term occurrence where the contribution from individual terms is assumed to be independent. The relevance pair (RP) model and the vector cosine (VC) model were compared and in the test environment improved retrieval was obtained with the RP model when compared with the VC model
- Imprint
- Medford, NJ : Learned Information Inc.
- Source
- Proceedings of the 55th Annual Meeting of the American Society for Information Science, Pittsburgh, 26.-29.10.92. Ed.: D. Shaw
-
Liddy, E.D.; Paik, W.; McKenna, M.; Yu, E.S.: ¬A natural language text retrieval system with relevance feedback (1995)
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- Abstract
- Outlines a fully integrated retrieval engine that processes documents and queries at the multiple, complex linguistic levels that humans use to construe meaning. Currently undergoing beta site trials, the DR-LINK natural language text retrieval system allows searchers to state queries as fully formed, natural sentences. The meaning and matching of both queries and documents is accomplished at the conceptual level of human expression, not by the simple concurrence of keywords. Furthermore, the natural browsing behaviour of information searchers is accomodated by allowing documents identified as potentially relevant by the explicit semantics of the system to be used as relevance feedback queries which provide an appropriate implicit semantic representation of the information seeker's need
- Imprint
- Medford, NJ : Learned Information
-
Srinivasan, P.: Query expansion and MEDLINE (1996)
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- Abstract
- Evaluates the retrieval effectiveness of query expansion strategies on a test collection of the medical database MEDLINE using Cornell University's SMART retrieval system. Tests 3 expansion strategies for their ability to identify appropriate MeSH terms for user queries. Compares retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a collection of 75 queries and 2.334 Medline citations. Recommends query expansions using retrieval feedback for adding MeSH search terms to a user's initial query
- Source
- Information processing and management. 32(1996) no.4, S.431-443
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Goffman, W.: ¬A searching procedure for information retrieval (1964)
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- Abstract
- A search procedure for an information retrieval system is developed whereby the answer to a question is obtained by maximizing an evaluation function of the system's output in terms of the probility of relevance. Necessary and sufficient conditions are given for a set to be an answer to a query. A partition of the file is made in such way that all documents belonging to the answer are members of the same class. Hence the answer can be generated by one relevant document. In this manner a search of the total file is avoided
- Source
- Information storage and retrieval. 2(1964), S.73-78
-
Lee, C.; Lee, G.G.: Probabilistic information retrieval model for a dependence structured indexing system (2005)
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- Abstract
- Most previous information retrieval (IR) models assume that terms of queries and documents are statistically independent from each other. However, conditional independence assumption is obviously and openly understood to be wrong, so we present a new method of incorporating term dependence into a probabilistic retrieval model by adapting a dependency structured indexing system using a dependency parse tree and Chow Expansion to compensate the weakness of the assumption. In this paper, we describe a theoretic process to apply the Chow Expansion to the general probabilistic models and the state-of-the-art 2-Poisson model. Through experiments on document collections in English and Korean, we demonstrate that the incorporation of term dependences using Chow Expansion contributes to the improvement of performance in probabilistic IR systems.
- Source
- Information processing and management. 41(2005) no.2, S.161-176
-
Gauch, S.; Smith, J.B.: ¬An expert system for automatic query reformation (1993)
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- Abstract
- Unfamiliarity with search tactics creates difficulties for many users of online retrieval systems. User observations indicate that even experienced searchers use vocabulary incorrectly and rarely reformulate their queries. To address these problems, an expert system for online search assistance was developed. This prototype automatically reformulates queries to improve the search results, and ranks the retrieved passages to speed the identification of relevant information. User's search performance using the expert system was compared with their search performance using an online thesaurus. The following conclusions were reached: (1) the expert system significantly reduced the number of queries necessary to find relevant passages compared with the user searching alone or with the thesaurus. (2) The expert system produced marginally significant improvements in precision compared with the user searching on their own. There was no significant difference in the recall achieved by the three system configurations. (3) Overall, the expert system ranked relevant passages above irrelevant passages
- Source
- Journal of the American Society for Information Science. 44(1993) no.3, S.124-136
-
Herrera-Viedma, E.; Cordón, O.; Herrera, J.C.; Luqe, M.: ¬An IRS based on multi-granular lnguistic information (2003)
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- Abstract
- An information retrieval system (IRS) based on fuzzy multi-granular linguistic information is proposed. The system has an evaluation method to process multi-granular linguistic information, in such a way that the inputs to the IRS are represented in a different linguistic domain than the outputs. The system accepts Boolean queries whose terms are weighted by means of the ordinal linguistic values represented by the linguistic variable "Importance" assessed an a label set S. The system evaluates the weighted queries according to a threshold semantic and obtains the linguistic retrieval status values (RSV) of documents represented by a linguistic variable "Relevance" expressed in a different label set S'. The advantage of this linguistic IRS with respect to others is that the use of the multi-granular linguistic information facilitates and improves the IRS-user interaction
