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

Design of an Interface for Page Rank Calculation using Web Link Attributes Information

This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment.HITS, Page Rank, Sel-HITS, Structure Mining

Role of Ranking Algorithms for Information Retrieval

As the use of web is increasing more day by day, the web users get easily lost in the web's rich hyper structure. The main aim of the owner of the website is to give the relevant information according their needs to the users. We explained the Web mining is used to categorize users and pages by analyzing user's behavior, the content of pages and then describe Web Structure mining. This paper includes different Page Ranking algorithms and compares those algorithms used for Information Retrieval. Different Page Rank based algorithms like Page Rank (PR), WPR (Weighted Page Rank), HITS (Hyperlink Induced Topic Selection), Distance Rank and EigenRumor algorithms are discussed and compared. Simulation Interface has been designed for PageRank algorithm and Weighted PageRank algorithm but PageRank is the only ranking algorithm on which Google search engine works.Comment: Keywords: Page Rank, Web Mining, Web Structured Mining, Web Content Minin

Enhancing Page Rank Algorithm

World Wide Web (WWW) is a collection of web Pages. A web Page consists of audio, Images, video, text etc. Retrieving web pages from large collection of WWW is a challenge. Web mining is used in extracting data from WWW. Web structure mining and web content mining plays an effective role in this approach. Page rank and weighted page rank algorithms are commonly used in the web structure mining, whereas HITS and weighted page content rank algorithms are used in the web structure mining and web content mining techniques. In this paper, a new algorithm is proposed, WPUCR (Weighted Page User Content Rank) algorithm which is a combination of web Usage Mining, web content mining and Web structure mining. It is the extension of weighted page content rank algorithm and shows the relevancy of the pages to a given query in a much more refined manner and works on the user behavior. DOI: 10.17762/ijritcc2321-8169.150518

Applications of concurrent access patterns in web usage mining

This paper builds on the original data mining and modelling research which has proposed the discovery of novel structural relation patterns, applying the approach in web usage mining. The focus of attention here is on concurrent access patterns (CAP), where an overarching framework illuminates the methodology for web access patterns post-processing. Data pre-processing, pattern discovery and patterns analysis all proceed in association with access patterns mining, CAP mining and CAP modelling. Pruning and selection of access pat-terns takes place as necessary, allowing further CAP mining and modelling to be pursued in the search for the most interesting concurrent access patterns. It is shown that higher level CAPs can be modelled in a way which brings greater structure to bear on the process of knowledge discovery. Experiments with real-world datasets highlight the applicability of the approach in web navigation

Study on Distance Measures for Clustering of Web Documents based on DOM-Tree based Representation of Web Document Structure

Among the three broad areas of Web mining, Web Structure Mining is the method of discovering structure information from either the web hyperlink structure or the web page structure. In order to apply data mining techniques on web pages, a good and efficient representation of web pages is required that could depict the actual hierarchical structure of web pages. The work presented here aims to find out an appropriate distance measure (also called as similarity measure) for strings that can be used for clustering of web documents and also for other data mining applications

A DOM-Tree based Representation of Web Document Structure for Web Mining Applications

Among the three broad areas of Web mining, Web Structure Mining is the method of discovering structure information from either the web hyperlink structure or the web page structure. In order to apply data mining techniques on web pages, a good and efficient representation of web pages is required that could depict the actual hierarchical structure of web pages. The work presented here aims to find out a representation of web documents that could be used as input for different data mining techniques. The present research work further aims at applying this representation for efficient clustering of web documents where clustering will be performed based on not only the web page content but also the structural layout of a web page

Using web mining in e-commerce applications

Nowadays, the web is an important part of our daily life. The web is now the best medium of doing business. Large companies rethink their business strategy using the web to improve business. Business carried on the Web offers the opportunity to potential customers or partners where their products and specific business can be found. Business presence through a company web site has several advantages as it breaks the barrier of time and space compared with the existence of a physical office. To differentiate through the Internet economy, winning companies have realized that e-commerce transactions is more than just buying / selling, appropriate strategies are key to improve competitive power. One effective technique used for this purpose is data mining. Data mining is the process of extracting interesting knowledge from data. Web mining is the use of data mining techniques to extract information from web data. This article presents the three components of web mining: web usage mining, web structure mining and web content mining.e-commerce, web mining, web content mining, web structure mining, web usage mining

Design of an Interface for Page Rank Calculation using Web Link Attributes Information

This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment