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example of possible cross-fertilization of these two fields, we examine the recent development of database keyword search (DBKWS). Even research in DBKWS is largely independent to GrC, DBKWS has to handle various issues related to granularity handling. In particular, aggregation of DBKWS results is closely related to studies
Search engine is one of the mostly-used big data applications. However, search system varies in different platforms and fields, and there are few approaches to evaluate its quality. Search engine for online shopping systems combines text search and classification-based retrieval. It is more difficult to validate and evaluate quality since there are no definite quality standards or testing methods...
The number of Web services are growing rapidly on the Internet. Topics of services are becoming various. Semantic-based keyword search is used to retrieve proper services for service consumers. According to the semantic information implied in service database, we build a topic model to cluster and management related
single machine. Our motivating application is recommenders, which typically deal with big numbers of users and items, but other applications might benefit as well, like keyword search. In this paper, we propose a parallel top-k MapReduce algorithm that, unlike existing MapReduce solutions, manages to handle cases in which
According to a report online [34], more than 200 million unique users search for jobs online every month. This incredibly large and fast growing demand has enticed software giants such as Google and Facebook to enter this space, which was previously dominated by companies such as LinkedIn, Indeed, Dice and CareerBuilder. Recently, Google released their “AIpowered Jobs Search Engine”, “Google For Jobs”...
. Keywords that occur in the title of patents are classified into three categories: Approach, Goal Object, and Goal Predicate, in order to create a model of relations of title patterns. The same keywords found on the timeline interval will be analyzed and illustrated in the patent pattern which are able to depict the
We collected 79,012 articles from 1916–2016 related to big data to determine which topics were being studied and how much of the literature was focused on privacy or security-related keywords. The analysis demonstrated that the big data paradigm commenced in late 2011 and the research production exponentially
becomes really difficult because name abbreviation, interdisciplinary, especially tautonym for Chinese scholars. The scholar classification can be achieved by the publications, journals that they published with, keywords in their publications using big-data techniques.
objects of non-interest. Then, with an inter-object attribute recognition technique, the relationships between objects are analyzed in terms of the degree, scope and nature of such relationships. As a result, the analysis of relevance between the information was based on certain keywords and used an inter-object relationship
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