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About 10,000 papers for “Web mining”

Web Mining

Henrik Hanke, Alf Neumann · IGI Global eBooks · 2011

The scale and scope of information on the Internet has been extended enormously over the past decade. The growth of more and more intelligent Web-based services and applications has resulted in an enormous growth of potentially useful data of both commercial and non-commercial interest. While this rise has brought a great amount of positive impact on global economic, social, and political development, it also implies an enormous flood of information into an increasingly complex information space. This is to be found on a vast variety of topics originating from a vast variety of sources, which range from private Web sites containing different kinds of information, to business-to-business B2B platforms. In most cases, these data are of an unsorted and unstructured kind, making efficient and target-oriented information retrieval very hard, if not nearly impossible. Coping with the challenge of a lack of transparency can be remedied by intelligent software agents, also referred to as softbots, which guide users through finding, sorting, and filtering this accruing data on the Internet like commonly used search engines.Request access from your librarian to read this chapter's full text.

Cited by 0Open access

Web Mining

Gonzalo Barría · 2020

Information on the Internet is growing exponentially every day. If the problem of political science in the 20th century was the lack of data to test hypotheses, the 21st century presents another challenge: information is abundant and within reach, but one has to know how to collect and analyze it. One of the most used techniques to extract information from websites is the technique known as web scraping. Web scraping is becoming an increasingly popular technique in data analysis because of its versatility in dealing with different websites. Before getting into the practice of web scraping one has to better understand what it is and how the robots.txt file present in most websites works. This file contains the so called robot exclusion standard which is a series of instructions specially directed to programs that seek to index the content of the pages (for example the Google bot that “saves” new pages that are created on the Internet).

Cited by 0

Web Mining

Roderick L. Lee · IGI Global eBooks · 2011

This chapter presents an overview of web mining. The three areas of web mining—Web content mining, Web usage mining, and Web structure mining—are identified. In this chapter specific attention is paid to Web structure mining, which is the study of the link topology. The link topology of the Web is analyzed in the context of a cyber-community in order to explore the connection between the link topology and conferral of authority. Millions, soon to be billions, of people are annotating Web documents, which results in an abundance of information. Herein lies the problem: topic distillation—searching through the sea of documents for relevant information. To address the problem of overabundance and relevancy, models are needed that can assist in creating order at the local level. The hub and spoke model identified in this chapter takes a proactive approach to creating an online community in a centralized or planned fashion and provides control over the architecture of the Web graph. In the end users can be assured with a certain level of confidence that the Web content contained in a hyperlinked community is both accurate and relevant.

Cited by 1

Web Mining

R. Walther · Informatik-Spektrum · 2001

Cited by 1

Web Mining

Sunkara Nagasivaanjaneya Reddy R · International Journal of Science and Research (IJSR) · 2023

Web-the name which is on the tip of everyone's tongue now a days and we all know it is the largest database in the world. The first recollection that we get when we think of it, is a vast Data Source where, finding the necessary data is a bit difficult. To overcome this problem and with the goal of providing user satisfaction the concept of Web Mining has been introduced. Simply, Web Mining is the Data Mining Techniques that are incorporated to manage WWW. The Web Mining research is at the crossroads of research from several communities such as database, sub areas of machine learning and natural language processing. However, there is a lot of confusion over the use of it when compared with various research views. But the Web Mining due to its vast size has found great scope of development. Keeping all these facts in mind, in this paper we elaborated on the types of Web Mining, its usage, popularityalong with its applications and limitations.Finally, we will conclude with some future directions to improve it for effective and efficient Data retrieval.

Cited by 0Open access

Web Mining

Ir R. Kosala, Ac. Be, R. Kosala et al. · 2007

The World Wide Web is an enormous information repository, but in order to efficiently access the information contained in it, sophisticated software is needed. This software is to a large extent based on data mining technology. In this section we start with a brief discussion of the nature of the Web and the specific problems encountered when trying to find information. We then give an overview of the many techniques that exist for web mining, illustrated with applications of these techniques. Note that with this overview we aim only at a high-level discussion of techniques; for a more thorough discussion we refer to [Kosala, 2000].

Cited by 0

Web Mining

Paolo Pelesk · Juraj Dobrila University of Pula Digital Repository · 2016

Rudarenje posjeta Web mjesta relativno je novo područje koje se sve češće koristi u poslovnim procesima i pri donošenju odluka. Rudarenje podataka koristi se u većini grana: sigurnost, promet, trgovine, medicina, itd. Dok metode i alati za rudarenje Weba pronalaze uporabu za otkrivanje korisničkih uzoraka s Web mjesta ili mobilne aplikacije. Alati i metode proizašle iz rudarenja podataka posebno su prilagođene za probleme rudarenja Weba. Rezultati rudarenja koriste se najčešće u poslovne svrhe a primjenu pronalaze u optimizaciji Web mjesta, u sustavima preporuka i personaliziranom sadržaju. Najpopularniji alati kao što su Google i Yahoo Analytics omogućili su korisnicima, koji mogu biti mala i srednja poduzeća, uvid u svoje korisnike i mogućnost mjerenja uspješnosti Web mjesta. Ovisno o problemu, rudarenje Weba rade stručnjaci uz posebne alate i često uz analizu sirovih podataka.

Cited by 0Open access

Web Mining

George J. Chang, Marcus J. Healey, James A. M. McHugh et al. · ˜The œKluwer international series on information retrieval · 2001

Cited by 4

Web mining

Kumbhar, VS, Oza, K S, Kamat, RK · CERN Document Server (European Organization for Nuclear Research) · 2016

Cited by 0

Web Mining

Alexander Linder · Deutscher Universitätsverlag eBooks · 2005

Cited by 0

Web Mining

The SAGE Encyclopedia of the Internet · 2018

Cited by 0

Integrating Semantic Web and Web Mining into Semantic Web Mining

Lisana BERBERI; Department of Informatics and Mathematics, University of Shkoder · Health and safety at work (Epoka University) · 2013

We know semantic web makes information more readable and meaningful to people bymaking it more understandable to machines and web mining is the application of data miningtechniques to discover patterns from the Web.We are aware websites on the Internet are increasing, daily, in size and complexity, whichmakes rather difficult that specific information, can be easily found.In this paper will be described how we can integrate semantic web and web mining intosemantic web mining.

Cited by 0Open access

Novel Web Usage Mining for Web Mining Techniques

Mahendra Pratap, Singh Dohare, Premnarayan Arya et al. · 2014

Abstract- Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigations of Web users. As in classical data mining, data processing and pattern discovery are the main issues in web usage mining. The first phase of the web usage mining is the data processing phase including session reconstruction. Session reconstruction is the most important task of web usage mining since it directly affects the quality of the extracted frequent patterns at the final step, significantly. Session reconstruction methods can be classified into two categories, namely 'reactive ' and 'proactive ' with respect to the data source and the data processing time. If the user requests are processed after the server handles them, this technique is called as ‘reactive’, while in ‘proactive ’ strategies this processing occurs during the interactive browsing of the web site. In this paper, we proposed a new reactive session reconstruction method. Our agent simulator models behavior of web users and generates web user navigations as well as the log data kept by the web server. In this way, the actual user sessions will be known and the successes of different techniques can be compared.

Cited by 0