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An automatic document classifier system based on ontology and the naive Bayes classifier is proposed in this paper. The main concept is to first establish a keyword synonymous table by experts for narrowing down the range and getting the consistency of keywords. The formal concept analysis is then used for
form of an ontology which represents the distinct areas of Software Engineering knowledge inspired by SWEBOK (Software Engineering Body of Knowledge). Finally, the process of the classification of texts within the ontology is carried out in three steps: keyword analysis, processing of the document. We believe our proposal
As the number of web services is increasing, finding the best service according to the users' requirements becomes a challenging task. Traditional method of web services discovery is based on keyword match. Due to this, many web services which are most relevant to the user request are left undiscoverable. Some other
Current classification techniques use word matching and clustering techniques to classify webpages. These techniques use ad hoc approach of checking and matching the entire keywords in a webpage for classification. These methods are efficient but not without problems. In general, they suffer from the following
into the server. Each of the file data or Web data is viewed as a memex event that can be described by 4W1H form. The memex event ontology is used to transform the various types of data to the standard 4W1H form. Users can view their life log chronologically and search them by keywords. Moreover, the life logs can be
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.