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This work addresses a novel spatial keyword query called the m-closest keywords (mCK) query. Given a database of spatial objects, each tuple is associated with some descriptive information represented in the form of keywords. The mCK query aims to find the spatially closest tuples which match m user-specified keywords
Searching published papers is a required activity for the researching process. Since articles are presented in various languages, it makes precise queries hard to achieve. In this paper, we propose an automatic theses clustering method based on bilingual and synonymous keyword sets which includes Chinese and English
Keyword search provides a simple yet effective way for the users to query and explore the underlying documents. In the recent years, there have been a great deal of research and development activities on extending keyword search capabilities to handle relational data, the dominant form in which business data are
A previously proposed keyword search paradigm produces, as a query result, a ranked list of object summaries (OSs); each OS summarizes all data held in a relational database about a particular data subject (DS). This paper further investigates the ranking of OSs and their tuples as to facilitate (1) the top-k ranking
With the increased demand for English communication, various styles of learning support methods have been proposed and provided to the Japanese learners. However, there are still many learners finding it hard to read, write and speak in English. Regardless of language difference, understanding the other's intention and emotional status accurately and expressing what they think or feel to the others...
Google Scholar is one of the major academic search engines but its ranking algorithm for academic articles is unknown. In a recent study we partly reverse-engineered the algorithm. This paper presents the results of our second study. While the previous study provided a broad overview, the current study focused on analyzing the correlation of an article's citation count and its ranking in Google Scholar...
Complex ad hoc join queries over enterprise databases are commonly used by business data analysts to understand and analyze a variety of enterprise-wide processes. However, effectively formulating such queries is a challenging task for human users, especially over databases that have large, heterogeneous schemas. In this paper, we propose a novel approach to automatically create join query recommendations...
Literature-based discovery for hypothesis generation is a subarea of text mining that aims to discover novel or previously-unknown knowledge from two complementary but disjoint (CBD) sets of literatures. The discovery approach is based on Swanson's discovery models where indirect connections between two disjoint sets of literatures A and C could be found through a set of common terms B extracted from...
the definition questions, the sentences or paragraphs with higher relevance can be extracted to become the answer based on the relevance ranking between the candidate sentences or paragraphs and questions by combined the computing method of keywords weighting and the method of semantic similarity between the sentences
The topic correlation judgment algorithm based on weight and threshold is proposed as for the problem that Web pages which are closely related to the given topic may be neglected due to not all keywords given by the users in the pages when users retrieve the topic they desire on the Internet. The algorithm retrieves
In this paper, we show how ontology can be utilized to support distant communication. Although augmented with audio and video functions, and screen sharing facilities, the users of real-time communication tools are facing difficulties due to their inability to provide appropriate meaning for keywords or conversation
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