Search logs are widely utilized in the research field of query expansion. However, traditional approaches focus on providing users with queries related to specific intentions and can only retrieve a limited amount of information from the World Wide Web. In this demonstration, we present CUE (Concept-level Understandable Explorer), a novel application that aims to discover concepts related to user queries that users do not expect. CUE mines interesting relationships between the smallest units of text (atoms or uni-grams) and incrementally combines the units into more integrated concepts. Additionally, concepts that share common search patterns are clustered to provide more search options. Our demonstration shows the feasibility of transferring real knowledge from the web to the user, giving them the ability to surf and not only query the web.

近年來，在幫助網路使用者修正查詢關鍵字的研究範疇中，搜尋引擎紀錄被廣泛得應用。然而，過去的研究注重提供使用者特定且準確的查詢推薦。這樣的研究只利用了部分的網路資訊。本研究期望能從多元的角度幫助使用者，讓她在找尋網路資訊時，能夠得到不曾想過的相關訊息，刺激她的聯想、幫助她快速釐清龐大的資訊。本研究提出了以語意概念為基礎的資訊探索引擎－CUE。我們將文字細分成小的語意單元，CUE可以分析語意單元之間的關連，並且漸進的把小單元整合成更完整的語意概念。更進一步地，CUE會依據語意概念的內涵，群聚擁有相似特徵的語意概念，藉此提供使用者更多元的查詢輔助。本研究證實了系統化的幫助使用者從網路整合資訊獲得知識是可行的。這樣的查詢輔助幫助使用者不僅僅搜尋網路的資訊，甚至遨遊在網路的知識之中。

[1] http://snowball.tartarus.org/.
[2] R. Baeza-yates, C. Hurtado, and M. Mendoza. Query recommendation using query logs in
search engines. In In International Workshop on Clustering Information over the Web (Clust-
Web, in conjunction with EDBT), Creete, pages 588–596. Springer, 2004.
[3] R. Baeza-Yates and A. Tiberi. Extracting semantic relations from query logs. In KDD ’07:
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and
data mining, pages 76–85, New York, NY, USA, 2007. ACM.
[4] H. Cao, D. Jiang, J. Pei, Q. He, Z. Liao, E. Chen, and H. Li. Context-aware query suggestion
by mining click-through and session data. In KDD ’08: Proceeding of the 14th ACM SIGKDD
international conference on Knowledge discovery and data mining, pages 875–883, New York,
NY, USA, 2008. ACM.
[5] J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. In OSDI
’04: Proceedings of the 6th Symposium on Operating Systems Design and Implementation,
pages 137–150, 2004.
[6] A. Fuxman, P. Tsaparas, K. Achan, and R. Agrawal. Using the wisdom of the crowds for
keyword generation. In WWW ’08: Proceeding of the 17th international conference on World
Wide Web, pages 61–70, 2008.
[7] N. Parikh and N. Sundaresan. Inferring semantic query relations from collective user behavior.
In CIKM ’08: Proceeding of the 17th ACM conference on Information and knowledge mining,
pages 349–358, New York, NY, USA, 2008. ACM.
[8] S. Sekine and H. Suzuki. Acquiring ontological knowledge from query logs. In WWW ’07:
Proceedings of the 16th international conference on World Wide Web, pages 1223–1224, New
York, NY, USA, 2007. ACM.
[9] E. M. Voorhees. Evaluating answers to definition questions. In NAACL ’03: Proceedings
of the 2003 Conference of the North American Chapter of the Association for Computational
Linguistics on Human Language Technology, pages 109–111, Morristown, NJ, USA, 2003.
Association for Computational Linguistics.