Proceedings of the 21st ACM International Conference on Information and Knowledge Management 2012
DOI: 10.1145/2396761.2398557
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Automatic query expansion based on tag recommendation

Abstract: We here propose a new method for expanding entity related queries that automatically filters, weights and ranks candidate expasion terms extracted from Wikipedia articles related to the original query. Our method is based on stateof-the-art tag recommendation methods that exploit heuristic metrics to estimate the descriptive capacity of a given term. Originally proposed for the context of tags, we here apply these recommendation methods to weight and rank terms extracted from multiple fields of Wikipedia artic… Show more

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Cited by 12 publications
(11 citation statements)
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“…Similarly, Oliveira et al. () introduced unsupervised tag recommendation methods to expand entity‐related queries from Wikipedia articles. Our framework has two main differences when compared with these.…”
Section: Related Workmentioning
confidence: 99%
“…Similarly, Oliveira et al. () introduced unsupervised tag recommendation methods to expand entity‐related queries from Wikipedia articles. Our framework has two main differences when compared with these.…”
Section: Related Workmentioning
confidence: 99%
“…Instead of using query log, the authors of [20] made use of existing keywords provided by social annotation services to generate and rank the new queries for suggestion. In the same line, the authors of [26] extracted candidate query terms from existing Wikipedia articles related to user query. In the context of image search, the work in [37] uses representative images for user to look ahead the search results of query terms.…”
Section: Related Workmentioning
confidence: 99%
“…The purpose of query reformulation is to provide additional information via query terms for users to reformulate their search intents. The terms are often ranked by different criteria such as co-occurrence patterns [20], latent topic model [5], and via knowledge bases [26]. The main difference between our work and the previous ones is that we rank the tags by their potential information towards reducing user effort.…”
Section: Introductionmentioning
confidence: 99%
“…Lin et al [14] extracted candidate expansion terms by a term-dependency method and ranked them based on social annotation resource. Oliveira et al [15] proposed to expand entityrelated queries using wikipedia articles and tag recommendation methods. Zhao et al [16] proposed an automatic diagnosis of term mismatch to guide interactive query expansion or create conjunctive queries.…”
Section: Related Workmentioning
confidence: 99%
“…Re-retrieval of new pages based on query expansion or reformulation is another effective strategy for improving retrieval accuracy, when initial search results in response to a query contain no pages relevant to users' search intentions. Query expansion or reformulation involves expanding or revising the search query to match additional or new pages by utilizing some technologies and information such as global analysis [9], pseudo-relevance feedback [10], users' personal information repository [11], term classification [12], hints obtained from external Web search engines [13], social annotation [14], wikipedia articles [15], and automatic diagnosis of term mismatch [16].…”
Section: Introductionmentioning
confidence: 99%