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In the past few years, there has been an exponential increase in the amount of information available on the World Wide Web. This plethora of information can be extremely beneficial for users. However, the amount of human intervention that is currently required for this is inconvenient. Information extraction (IE) systems try to solve this problem by making the task as automatic as possible. Most of...
desirable. In this paper, some existing achievements are investigated firstly. Then our current technique on web information extraction is discussed in detail. In our approach, rules and patterns are extracted from sample pages through training process, with human involvements. We use both keywords and regular expressions to
5th GrC model is the formal model specified into the category of sets. It is a theory of ordered granules, namely, granules are ordered ldquosubsetsrdquo of the universe, We extract a 5th GrC model from a set of Web pages. A granule is a high frequent sequence of keywords, It is a tuple in a relation and naturally
Traditional automatic classifiers often conduct misclassifications. Folksonomy, a new manual classification scheme based on tagging efforts of users with freely chosen keywords can effective resolve this problem. Even though the scalability of folksonomy is much higher than the other manual classification schemes, the
With this research we present a system that suggests valuable complementary information relevant to a user's topic of interest, in the form of keywords. For this purpose we have automatically constructed a Web search directory called TORISHIKI-KAI from a large collection of Web documents, using state of the art
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