• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.161-167
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• 2012

Query reformulation is an interactive process of revising user queries according to the query results. To assist biomedical researchers in this process, we present novel methods for automatically generating query reformulation suggestions. While previous work on query reformulation focused on addition of words to user queries, our method can deal with three types of query reformulation (i.e., addition, removal and replacement). The accuracy of the method for the addition type is ten times better than PubMed's "Also try", while the execution time is short enough for practical use.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.37-60
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• 2010

The purpose of this study is to investigate image search query reformulation patterns in relation to image attribute categories. A total of 592 sessions and 2,445 queries from the Excite Web search engine log data were analyzed by utilizing Batley's visual information types and two facets and seven sub-facets of query reformulation patterns. The results of this study are organized with two folds: query reformulation and categorical transition. As the most dominant categories of queries are specific and general/nameable, this tendency stays over various search stages. From the perspective of reformulation patterns, while the Parallel movement is the most dominant, there are slight differences depending on initial or preceding query categories. In examining categorical transitions, it was found that 60-80% of search queries were reformulated within the same categories of image attributes. These findings may be applied to practice and implementation of image retrieval systems in terms of assisting users' query term selection and effective thesauri development.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.963-972
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• 1997

In imformation retrival, query reformulation algorithms construct querise from a set of intial input and feedback documents, and retrieval performance cna be varied by different sets of input documents. In this study, we developed a criterion for measuring the performance sensitivity of query reformulation algorithms to unput sets. In addition, we also propose a way of mesuring the changes in retrived area, (CIRA) during qucry reformulation. We cimpared CIRAs of query refromulation algorithms (i.e., query tree, DNF method, and Dillon's method) using three test sets:the CACM, CISI, and Medlars. In the experiments, the query tree showed the highest decreasing CIRA during refirmulations, which means the fastest convergence rate to an output set. For sensitivity analysis, the query tree sored the highest sensitivity to different input sets even though its differences to the tther algorithms are very small.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.141-149
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• 1998

One of the difficulties in using the current Boolean-based information retrieval systems is that it is hard for a user, especially a novice, to formulate an effective Boolean query. One solution to this problem is to let the system formulate a query for a user from his relevance feedback documents in this research, an intelligent query reformulation mechanism based on ID3 is proposed and the sensitivity of its retrieval effectiveness, i.e., recall, precision, and E-measure, to various input settings is analyzed. The parameters in the input settings is the number of relevant documents. Experiments conducted on the test set of Medlars revealed that the effectiveness of the proposed system is in fact sensitive to the number of the initial relevant documents. The case with two or more initial relevant documents outperformed the case with one initial relevant document with statistical significances. It is our conclusion that formulation of an effective query in the proposed system requires at least two relevant documents in its initial input set.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.419-419
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• 1996

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.61-79
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• 2006

To come up with the recommendations to improve the patent & trademark retrieval efficiency, 100,016 patent & trademark search requests by 17,559 unique users over a period of 193 days were analyzed. By analyzing 2,202 multi-query sessions, where one user issuing two or more queries consecutively, we discovered a number of retrieval efficiency improvements clues. The session analysis result also led to suggestions for new system features to help users reformulating queries. The patent & trademark retrieval users were found to be similar to the typical web users in certain aspects especially in issuing short queries. However, we also found that the patent & trademark retrieval users used Boolean operators more than the typical web search users. By analyzing the multi-query sessions, we found that the users had five intentions in reformulating queries such as paraphrasing, specialization, generalization, alternation, and interruption, which were also used by the web search engine users.

• Journal of the Korean Society for information Management
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• v.13 no.1
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• pp.103-117
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• 1996

The purpose of this study is to identify how users react with the search options and bibliographic information during search reformulation on the online catalog. Two online catalogs(N0TIS system and Dynix system) were selected and undergraduate students were recruited as the participants for this study. The study shows that the search options and bibliographic information affected the type of the query reformulation and the re-choice of the search options during search.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.88-98
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• 2000

Cooperative query answering provides neighborhood or associate information relevant to the initial query using the knowledge about the query and data. In this paper, we present an intelligent query answering system for suporting cooperative query answering system presented in this paper performs query relaxation process using hybrid knowledge base. The hybrid knowledge base which is used for relaxation of queries, composes of semantic list and rule based knowledge base for structural approach. Futhermore, this paper proposes the query relaxation algorithm for query reformulation using initial query on the basis of hybrid knowledge base.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.659-665
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• 2001

Relevance feedback is the most popular query reformulation strategy in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.9-14
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• 2002

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.