Multiple sets of features for automatic genre classification of web documents

نویسندگان

  • Chul Su Lim
  • Kong Joo Lee
  • Gil-Chang Kim
چکیده

With the increase of information on the Web, it is difficult to find desired information quickly out of the documents retrieved by a search engine. One way to solve this problem is to classify web documents according to various criteria. Most document classification has been focused on a subject or a topic of a document. A genre or a style is another view of a document different from a subject or a topic. The genre is also a criterion to classify documents. In this paper, we suggest multiple sets of features to classify genres of web documents. The basic set of features, which have been proposed in the previous studies, is acquired from the textual properties of documents, such as the number of sentences, the number of a certain word, etc. However, web documents are different from textual documents in that they contain URL and HTML tags within the pages. We introduce new sets of features specific to web documents, which are extracted from URL and HTML tags. The present work is an attempt to evaluate the performance of the proposed sets of features, and to discuss their characteristics. Finally, we conclude which is an appropriate set of features in automatic genre classification of web documents. 2004 Elsevier Ltd. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Learning to classify documents according to genre

Current document retrieval tools succeed in locating large numbers of documents relevant to a given query. While search results may be relevant according to the topic of the documents, it is more difficult to identify which of the relevant documents are most suitable for a particular user. Automatic genre analysis that is, the ability to distinguish documents according to style would be a usefu...

متن کامل

شناسایی خودکار سبک موسیقی

Nowadays, automatic analysis of music signals has gained a considerable importance due to the growing amount of music data found on the Web. Music genre classification is one of the interesting research areas in music information retrieval systems. In this paper several techniques were implemented and evaluated for music genre classification including feature extraction, feature selection and m...

متن کامل

Thesis Stereotyping the Web: Genre Classification of Web Documents

OF THESIS STEREOTYPING THE WEB: GENRE CLASSIFICATION OF WEB DOCUMENTS Retrieving relevant documents over the Web is a difficult task. Currently, search engines rely on keywords for matching documents to user queries. This paper explores the potential for discriminating documents based on the genre of the document. I define genre as a taxonomy that incorporates the style, form and content of a d...

متن کامل

An Improvement in Support Vector Machines Algorithm with Imperialism Competitive Algorithm for Text Documents Classification

Due to the exponential growth of electronic texts, their organization and management requires a tool to provide information and data in search of users in the shortest possible time. Thus, classification methods have become very important in recent years. In natural language processing and especially text processing, one of the most basic tasks is automatic text classification. Moreover, text ...

متن کامل

Musical genre classification of audio signals

Musical genres are categorical labels created by humans to characterize pieces of music. A musical genre is characterized by the common characteristics shared by its members. These characteristics typically are related to the instrumentation, rhythmic structure, and harmonic content of the music. Genre hierarchies are commonly used to structure the large collections of music available on the We...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Inf. Process. Manage.

دوره 41  شماره 

صفحات  -

تاریخ انتشار 2005