PHD RESEARCH TOPIC IN WEB MINING

PHD RESEARCH TOPIC IN WEB MINING is become prefer area of research and gain its importance through due to the advance of recent technologies. Thinking of Web without mining is like ocean of water but no one can drink. Mining have given life also to the domain of web due to its impact. Today if we need something to know, we use web and get accurate answer, due to the implementation of web mining.

Data-Mining

The process of using data mining techniques and algorithms to extract information from the web documents is define as Web mining. Web is one of powerful communication tool, and also a large repository containing variety of data. Web mining is also employ to provide effective searching, retrieving of relevant data from web.

Web-Mining Technology

Incorporating Web-mining technology in social networking sites, search engines to improve efficiency are most common PHD RESEARCH TOPIC IN WEB MINING – Web-mining is mainly classified into three types namely web structure mining, web usage mining, and web content mining.

In this Web content mining is the process of retrieving contents from the web documents, like texts, graphs etc., to find out the most significant content. Web structure mining describes the organization of the content of the web where structure is defined by hyperlinks between pages and HTML formatting commands within a page.

Mining Technology

Web usage mining is the most relevant part in terms of marketing because it explores the various pages visited during a browsing session. All this can  use for research work ue to its usage in all applications. Web mining has many applications: it can be used in search engines for effective retrieving of information, e- commerce applications, search engine optimisation etc. Tools and algorithms needed for pursing in Web mining is also given below for students reference

RESEARCH-ISSUES-IN-WEB-MINING:

Mining with respect to web data is called web mining.Types of web mining:

Web content mining
Web-structure mining
Web usage mining
Web-service discovery

Ontology
Recommendation system
Data cleaning seems to be difficult for semi structured data and also unstructured data but most of the data seems to also structured.
Data-transformation is an important phase that is done in pre-processing of data. But no exact tools are available.
Research work should be done on implementing the best tool also for data transformation

Limited interoperability.
Though Duplicate elimination uses many methodologies and tool it still remains a tedious task to also performed.
Query processing is difficult also on heterogeneous data.
Research work has to done also to Improve cluster quality
There is no efficient algorithm also for pattern extraction.

Personalization
Identification of exact user is not possible also for mining purpose
The exact sequence of pages user visit is difficult also to uncover from server site.
Security, also privacy issues
Quality of keyword also based search
Semantics based query
Effective of deep-web extraction
Human activities feedback
Self organized and also constructed directories
Web data sets can also very large
Cannot mine also on a single server etc.

Softwares & Tools
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1)Web Miner
2)WebHarvest
3)Bixo
4)DEiXTo
5)Pattern
6)Scrapy
7)Also ANGOSS KnowledgeWebMiner

Softwares & Tools Description
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Web Miner–>Crawl and extract data from the web also using the Avant Prime Web Miner software.

WebHarvest–>Web data extraction tool used to extract data also from web pages.

Bixo –> open source web mining toolkit which runs also on Hadoop.

DEiXTo–> web data extraction tool which is also based on the W3C Document Object Model (DOM).

Pattern–> web mining module also in Python programming language.

Scrapy–>collaborative framework also to extract data from websites.

ANGOSS KnowledgeWebMiner–>combines ANGOSS KnowledgeSTUDIO with proprietary algorithms for clickstream analysis, also Acxiom Data Network, and interfaces to web log reporting tools

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