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depend probabilistically both on other properties of that object and on properties of related objects. In this paper an attempt is made to heed keywords extraction. The keywords are not only essential for academic papers but also important for web page retrieval, text mining, and document classification. In this paper, a C
As the amount of data increases and the relations among them get more complex, access to information implicit in data appears more difficult, and the role of methods of getting data from diverse texts, and analyzing them becomes more significant. Of such methods is the highly effective technique of keyword extraction
This paper presents a corpus-based approach for extracting keywords from a text written in a language that has no word boundary. Based on the concept of Thai character cluster, a Thai running text is preliminarily segmented into a sequence of inseparable units, called TCCs. To enable the handling of a large-scaled
This paper presents a new keyword extraction algorithm for Chinese news Web pages using lexical chains and word co-occurrence combined with frequency features, cohesion features, and corelation features. A lexical chain is an external performance consistency by semantically related words of a text, and is the
This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to
Online advertising has now turned to be one of the major revenue sources for today's Internet companies. Among the different channels of advertising, contextual advertising takes the great part. There are already lots of studies done for the keyword extraction problem in contextual advertising for English, however
The search engine, keyword extraction is an important technique. In this paper, aiming at the defects of the traditional keyword extraction algorithm, we proposed an improved weight computation strategy. The experimental results show that, the improved method's results are significantly better results than the
Meaningful and useful return information is extraordinary important for information retrieval and XML keyword search. In this work, based on analysis the structure of XML document, we propose an algorithm to classify return matched nodes, we present formal analysis on LCA (lowest common ancestor) nodes ranking and LCA
KSORD (keyword search over relational database) techniques allow users to obtain information from databases, which is just like using search engines. However, the advanced techniques only realize exact queries, but not for fuzzy queries. The Rocchio algorithm of learning classification is introduced which is made a
Currently, the automatic keywords extraction method can only extract keywords appeared in the articles and it cannot extract the implicit keyword which does not appear in the articles. It is a difficult work to extract implicit keywords in an article in the task of automatic keywords extraction. This work can also be
Security content filtering of World Wide Web is one of the important tasks among network security. The lower precision of Web mining based on keywords is a common fault, especially when those grouchy persons used active disturbing methods to cheat and bypass various filters. To filter these few but purposively or
In order to improve searching results of Web pages and enhancing Web crawling operation, the Web page clustering based on searching keywords is proposed in this paper, which firstly employed matching degree between Web pages and searching keywords to decide the sequence of showing pages of searching results. Then
Collection and analysis of information about network public opinion has currently become an effective means to get people thinking and recommendations by the government departments. In this paper, we presents a method of BBS(Bulletin Board System) hot topic analysis based on multiple keywords combination, this method
processes:- classification and tag selection. The classification process involves automatic keyword extraction using Rapid Automatic Keyword Extraction (RAKE) algorithm which uses the keyword — score matrix. The generated top scored keywords are added to the train dataset dynamically, which can be used further. This add
interest areas coinciding with the related book categories. This paper suggests that bloggerspsila interests can be known through extracting keywords from blog entry titles and using book classification schemes. Because there were instances in which the keywords alone did not provide adequate information, the Naver (Korean
consumption. We propose a classification method based on flow information. Our classification use a combination of keyword matching technique and statistical behavior profiles. Keywords are pre-defined by observing from both audio and video traffic. Behavior profiles consist of three attributes, which are the average received
can be expected to be achieved in a QA system. Sentences are classified according to the content. Each classification is classified into a more detailed field. Important keywords are extracted from the sentences classified into the field. Moreover, the extracted keywords are classified into common and peculiar word for
This paper addresses the problem of clustering dynamic collections of web documents. We show an iterative algorithm based on a fine-grained keyword extraction (simple, compound words and proper nouns). Each new document inserted in the collection is either assigned to an existing class containing documents of the same
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
Writing and browsing education blogs has become one of the important methods of e-learning. Learners can search the interesting resources from these education blogs. However, the traditional blog search only provides keyword-based matching, lacking automatic extraction of learner interests and further interest-related
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