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This paper proposes an extended vector space model (VSM), which is called M2VSM (meta keyword-based modified VSM). When conventional VSM is applied to document clustering, it is difficult to adjust the granularity of cluster in terms of topic. In order to solve the problem, M2VSM considers meta keywords such as
Due to its considerable ease of use, relational keyword search (R-KWS) has become increasingly popular. Its simplicity, however, comes at the cost of intensive query processing. Specifically, R-KWS explores a vast search space, comprised of all possible combinations of keyword occurrences in any attribute of every
based on keyword indexing, there are many records in their result lists that are irrelevant to the user's information needs. It is shown that for retrieving more relevant and precise results, the following two points should be concerned: First of all, the query (either it is generated by a human or an intelligent agent
taken into account when indexing documents and when performing searching. Utilizing this approach, it is possible to use a natural language to express user queries. In many cases, this way is more usual for users to describe their information needs compared to the keyword style. The factoid question answering task is one
multimedia user-generated content. An authorized person or body filters it before being published. Once user-generated multimedia tourist contents are accepted, they are published using a tool into a web page. This GUI allows browsing for contents provided by individual users or those including a tag or keyword. Finally, the
Message Oriented Middleware (MOM) is getting popular along with the development of heterogeneous platforms and applications. Most Message Oriented Middleware supports Publish/Subscribe scheme for message interoperation and it usually matches topics directly by matching keywords. Recent Semantic Message Oriented
Traditional image classification techniques are based on the analysis of low-level visual features or on textual information. In this paper, we describe a novel solution which tries to improve image analysis and processing algorithms by incorporating keywords and textual annotation produced by humans in a folksonomy
sets of keywords is used and a dynamic approach is presented for updating the semantic network and semantic contents of the images in an interactive way. The proposed approach, certainly, executes a novel kind of long term learning-based on user's opinion in the several interactions with system, and relates the behavior
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.