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Efficiently answering XML keyword queries has attracted much research effort in the last decade. The key factors resulting in the inefficiency of existing methods are the common-ancestor-repetition (CAR) and visiting-useless-nodes (VUN) problems. To address the CAR problem, we propose a generic top-down processing strategy to answer a given keyword query w.r.t. LCA/SLCA/ELCA semantics. By “top-down”,...
Many researchers have recognized Wikipedia as a resource of huge dynamic knowledge base in recent years. This paper provides a new approach for obtaining measures of terms semantic relatedness, which maps terms to relevant Wikipedia articles as the background information for analyzing. The proposed algorithm WLA focuses on the hyperlink structure and summary paragraph extracted from the topic pages...
Mining based on opinions can extract useful information from users' comments. After doing cluster and analysis on the information, users can get a detailed understanding of the commodity, then determine to buy the commodity or not. In this paper, firstly, we extract evaluation objects and evaluation words, then cluster the evaluation objects. Next based on SO-PMI algorithm, judge the polarity of evaluation...
Search engines have become the main way for people to get expected information, most of them are based on keyword search. However, keyword search is based on computing the similarity of letters of the keywords, instead of semantic meaning, therefore the searching results often include irrelevant information to user intention. This paper aims to find a way on improving keyword search efficiency. Using...
With increment of personal data amount, how to allow users to efficiently re-find personal data items becomes an important research issue. According to general experience of persons, task is taken as a popular way to classify personal dataset, and is often taken as a factor to re-access expected items. In this paper, we propose a framework called TaskSpace to help users re-find expected data items...
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