Document (#40186)

Author
Vidinli, I.B.
Ozcan, R.
Title
New query suggestion framework and algorithms : a case study for an educational search engine
Source
Information processing and management. 52(2016) no.5, S.733-752
Year
2016
Abstract
Query suggestion is generally an integrated part of web search engines. In this study, we first redefine and reduce the query suggestion problem as "comparison of queries". We then propose a general modular framework for query suggestion algorithm development. We also develop new query suggestion algorithms which are used in our proposed framework, exploiting query, session and user features. As a case study, we use query logs of a real educational search engine that targets K-12 students in Turkey. We also exploit educational features (course, grade) in our query suggestion algorithms. We test our framework and algorithms over a set of queries by an experiment and demonstrate a 66-90% statistically significant increase in relevance of query suggestions compared to a baseline method.
Content
Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457316300073.
Theme
Suchmaschinen
Semantisches Umfeld in Indexierung u. Retrieval

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