An unsupervised technical difficulty ranking model based on conceptual terrain in the latent space

Authors:
Shoaib Jameel;Wai Lam;Xiaojun Qian;Ching-man Au Yeung
Affiliations:
The Chinese University of Hong Kong, Hong Kong, Hong Kong;The Chinese University of Hong Kong, Hong Kong, Hong Kong;The Chinese University of Hong Kong, Hong Kong, Hong Kong;ASTRI, Hong Kong, Hong Kong
Venue:
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Year:
2012

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Ranking Text Documents Based on Conceptual Difficulty Using Term Embedding and Sequential Discourse Cohesion

WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01

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Abstract

Search results of the existing general-purpose search engines usually do not satisfy domain-specific information retrieval tasks as there is a mis-match between the technical expertise of a user and the results returned by the search engine. In this paper, we investigate the problem of ranking domain-specific documents based on the technical difficulty. We propose an unsupervised conceptual terrain model using Latent Semantic Indexing (LSI) for re-ranking search results obtained from a similarity based search system. We connect the sequences of terms under the latent space by the semantic distance between the terms and compute the traversal cost for a document indicating the technical difficulty. Our experiments on a domain-specific corpus demonstrate the efficacy of our method.