dc.contributor.authorWong, Hsiu Yun.
dc.description.abstractThe internet is a great source of database that contains valuable information of all kind. Weblogs or blogs has been one of the most popular and greatly growing communication tools on the internet. With many people sharing and discussing on different topic, many valuable information can be attain from it. However, with many blog providers on the internet providing free space for people to host their blog or discuss on topics, the number of people “blogging”, has grown exponentially. The problem is, most of the time, blogger can post entry on any topic anytime they want. Although some blog does categories the entries posted or have different categories for the user to post their topic on, most off the categories are either too general or the user might just post their topic on any categories which is not related at all. This resulted in time wasted on going through unnecessary entries and most of the time user will be spending more time on searching what they want to read then reading it. Therefore, weblog content classification program was created to ease the user the browsing and reading of interested entries. However, in order to classify the content more specifically to the user desired categories, the involvement of the user judgment on the keywords related to the categories will be required. For this project, an open source web scrapper tool Web-Harvest was intergraded with the program to extract the required desired blog contents for classification.en_US
dc.format.extent110 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen_US
dc.titleWeb blog content classificationen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorWang Lipoen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US

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