A Review Of Trends In Research On Web Mining

In recent years the growth of the World Wide Web exceeded all expectations. Today there are several billions of HTML documents, pictures and other multimedia files available via internet and the number is still rising. But considering the impressive variety of the web, retrieving interesting content has become a very difficult task.So, the World Wide Web is a fertile area for data mining research.Web mining is a research topic which combines two of the activated research areas: Data Mining and World Wide Web. Web mining research relates to several research communities such as Database, information Retrieval and Artificial intelligence, visualization.This paper reviews the research and application issues in web mining besides proving an overall view of Web mining

A Model for Personalized Keyword Extraction from Web Pages using Segmentation

The World Wide Web caters to the needs of billions of users in heterogeneous groups. Each user accessing the World Wide Web might have his / her own specific interest and would expect the web to respond to the specific requirements. The process of making the web to react in a customized manner is achieved through personalization. This paper proposes a novel model for extracting keywords from a web page with personalization being incorporated into it. The keyword extraction problem is approached with the help of web page segmentation which facilitates in making the problem simpler and solving it effectively. The proposed model is implemented as a prototype and the experiments conducted on it empirically validate the model's efficiency.Comment: 6 Pages, 2 Figure

Web Mining Functions in an Academic Search Application

This paper deals with Web mining and the different categories of Web mining like content, structure and usage mining. The application of Web mining in an academic search application has been discussed. The paper concludes with open problems related to Web mining. The present work can be a useful input to Web users, Web Administrators in a university environment.Database, HITS, IR, NLP, Web mining

Development of the CODER System: A Test-bed for Artificial Intelligence Methods in Information Retrieval

The CODER (COmposite Document Expert/Extended/Effective Retrieval) system is a test-bed for investigating the application of artificial intelligence methods to increase the effectiveness of information retrieval systems. Particular attention is being given to analysis and representation of heterogeneous documents, such as electronic mail digests or messages, which vary widely in style, length, topic, and structure. Since handling passages of various types in these collections is difficult even for experimental systems like SMART, it is necessary to turn to other techniques being explored by information retrieval and artificial intelligence researchers. The CODER system architecture involves communities of experts around active blackboards, accessing knowledge bases that describe users, documents, or lexical items of various types. Most of the lexical knowledge base construction work is now complete, and experts for search and temporal reasoning can perform a variety of processing tasks. User information and queries are being gathered, and the first prototype is nearly complete. It appears that a number of artificial intelligence techniques are needed to best handle such common, but complex, document analysis and retrieval tasks

Fourth ABC Index and Fifth GA Index of Certain Special Molecular Graphs

Several chemical indices have been introduced in theoretical chemistry to measure the properties of molecular structures, such as atom bond connectivity index and geometric-arithmetic index. In this paper, we present the fourth atom bond connectivity index and fifth geometric-arithmetic index of fan molecular graph, wheel molecular graph, gear fan molecular graph, gear wheel molecular graph, and their r-corona molecular graphs