Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval

Kumar, Mrinal

doi:10.3844/ajassp.2010.840.845

Cited by 30 publications

(16 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There are several methods that can be used in order to perform the link analysis that includes PageRank, Weighted PageRank, HITS algorithms and others [35]. The link analysis can conducted in a context based analysis of the search query which will be store as a separate graph.…”

Section: Discovered Linksmentioning

confidence: 99%

A Robust Framework for Web Information Extraction and Retrieval

Alfred¹,

Soon²,

On³

et al. 2014

IJMLC

View full text Add to dashboard Cite

Abstract-The large volume of online and offline information that is available today has overwhelmed users' efficiency and effectiveness in processing this information in order to extract relevant information. The exponential growth of the volume of Internet information complicates information access. Thus, it is a very time consuming and complex task for user in accessing relevant information. Information retrieval (IR) is a branch of artificial intelligence that tackles the problem of accessing and retrieving relevant information. The aim of IR is to enable the available data source to be queried for relevant information efficiently and effectively. This paper describes a robust information retrieval framework that can be used to retrieve relevant information. The proposed information retrieval framework is designed to assist users in accessing relevant information effectively and efficiently as it handles queries based on user preferences. Each component and module involved in the proposed framework will be explained in terms of functionality and the processes involved.Index Terms-Information retrieval, information retrieval framework, semantic web. I. INTRODUCTIONInformation retrieval (IR) is a process that extracts and retrieves information that is relevant to user based on the queries posted. IR deals with many aspects including the representation, storage, organization and retrieving information from data sources. Furthermore, these data sources can be accessed offline or online and they can be categorized into structured, semi-structured or unstructured data. The origin of the IR research can be traced back to ancient times when librarians kept information related to articles or books using catalogue cards [1], [2] and earlier works related to information retrieval can be found in 1950 [3]. The advent of computer has brought the IR system to a new level as computers are capable of processing large volume of data in order to extract and retrieve relevant information [4]. The increase of capacity and computational power has contributed to the rapid growth of unstructured data. For instance, with the advent of World Wide Web(WWW) making the information available online through hyperlink, the research attention of IR have been Rayner Alfred, Gan Kim Soon, and Chin Kim On are with the COESA, Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, g_k_s967@yahoo.com, kimonchin@ums.edu.my).Patricia Anthony is with the Department of Applied Computing, Faculty of Environment, Society and Design, Lincoln University, Christchurch, New Zealand (e-mail: patricia.anthony@lincoln.ac.nz).shifted to Web IR and it is increasingly gaining popularity. Among significant IR tools for WWW IR are the search engines. In order to retrieve information from the WWW, search engines with different capabilities and algorithm shave been developed. However, the advancement of Internet made information available growth exponential through time and a robust framework for web information extraction and retrieval is critically required to pro...

show abstract

Section: Discovered Linksmentioning

confidence: 99%

A Robust Framework for Web Information Extraction and Retrieval

Alfred¹,

Soon²,

On³

et al. 2014

IJMLC

View full text Add to dashboard Cite

show abstract

“…Web structure mining discovers knowledge from hyperlinks, which represent the structure of the Web. (Kumar and Singh, 2010) presented a study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval. Web Usage Mining (WUM) mines the data that describes the pattern of usage of Web pages, such as IP addresses, page references and the date and time of accesses.…”

Section: Web Usage Miningmentioning

confidence: 99%

IPACT: Improved Web Page Recommendation System Using Profile Aggregation Based On Clustering of Transactions

Almurtadha¹,

Sulaiman²,

Mustapha³

et al. 2011

American Journal of Applied Sciences

View full text Add to dashboard Cite

Problem statement: Recently, Web usage mining techniques have been widely used to build recommendation systems especially for anonymous users. Approach: Assigning the current user to the best web navigation profile with similar navigation activities will improve the ability of the prediction engine to produce a recommendation list then introduce it to the user. This study presents iPACT an improved recommendation system using Profile Aggregation based on Clustering of Transactions (PACT). Results: iPACT shows better prediction accuracy than the previous methods PACT and Hypergraph. Conclusion: The users' interests change over time; hence an incremental and adaptive web navigation profiling is a key feature for the future works.

show abstract

“…Web Usage Mining and Web Structure Mining (Kumar and Singh, 2010) are playing a crucial role to implement such recommendation system. Web Usage Mining (Kosala and Blockeel, 2010) is the discovery of web server access pattern.…”

Section: Introductionmentioning

confidence: 99%

An Ontology Based Approach to Implement the Online Recommendation System

Mohanraj¹

2011

Journal of Computer Science

View full text Add to dashboard Cite

Problem statement: Every web user has different intent when accessing the information on website. The primary goal of recommendation system is to anticipate the user intent and recommend the web pages that contain user expected information. Effective recommendation of web pages involves two important challenges: accurately identifying the user intent and predict the result show that novel web usage mining method and ontological concept scoring algorithm based on website domain ontological profile helps the recommendation system imminent navigation pattern in such a way that it provides required content while users browse the predicted navigation. Approach: We present a ontology based approach to implement recommendation system that involves applying innovative web usage mining on log system to discover all possible imminent navigation patterns of current user and resolve any uncertainties in discovering the navigation pattern by applying ontological concept based similarity comparison and scoring algorithm. Results: result show that novel web usage mining method and ontological concept scoring algorithm based on website domain ontological profile helps the recommendation system to predict and present most relevant navigation pattern to users. Conclusion: our recommendation system confirms that ontology based approach should be used to ensure excellent accuracy in predicting and capturing future navigation pattern of web user.

show abstract

Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval

Cited by 30 publications

References 14 publications

A Robust Framework for Web Information Extraction and Retrieval

A Robust Framework for Web Information Extraction and Retrieval

IPACT: Improved Web Page Recommendation System Using Profile Aggregation Based On Clustering of Transactions

An Ontology Based Approach to Implement the Online Recommendation System

Contact Info

Product

Resources

About