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Data Mining Algorithms for Knowledge Extraction from web log files 1

2nd International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD)

作者： El Alami, Anass Abdelhamid Ezzikouri, Hanane Erritali, Mohammed Sultan Moulay Slimane Univ Fac Sci & Technol Comp Sci Dept TIAD Lab BP 523 Beni Mellal Morocco Sultan Moulay Slimane Univ Fac Sci & Technol Math Dept LMACS Lab BP 523 Beni Mellal Morocco

ISBN: (数字)9783030366537

ISBN: (纸本)9783030366537;9783030366520

web log files contain visitor activity information on a website. They are automatically created and maintained by a web server. The raw web log file format is essentially one line of text for each visit of the web site, each time a visitor requests a page (HTML document, image, etc.), information about the request (including client IP address, request date/time, page requested, HTTP code, bytes served, user agent, and referrer) are added to the current log file. The web maintains a standard format the CLF (Common log Format) for web server log files. Analysis of server log file can provide significant and useful information, data extracted from log files could be stored in a database, allowing various uses when needed. Data Mining is the process of extracting and discovering patterns and knowledge from large amounts of data. web Mining is the extraction of interesting and potentially useful patterns and implicit information from artifacts or activity related to the web. web Usage Mining is a main research area in web mining focused on learning about web users and their interactions with web sites. It is the application of data mining techniques to discover usage patterns from web data. In this paper, we present an analysis and extraction of useful information and patterns from web data based on a deep analysis of web log files, first we start with the presentation of different formats of web log files, then we present the different preprocessing used methods, finally the demonstration of the system "web content and Usage Mining'' for extracting knowledge from web data and web site analysis using several Data Mining Algorithms Apriori, FPGrowth, K-Means, KNN, and ID3.

关键词： web mining Data mining web usage mining web log file Data cleaning Preprocessing

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Efficient Management of web Data by Applying web Mining Pre-processing Methodologies 50th

Efficient Management of Web Data by Applying Web Mining Pre-...

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50th Annual Convention of the Computer-Society-of-India (CSI) on Digital Life

作者： Kaur, Jaswinder Garg, Kanwal Kurukshetra Univ Dept Comp Sci & Applicat Kurukshetra Haryana India

ISBN: (纸本)9789811088483;9789811088476

web usage mining is defined as the application of data mining techniques to extract interesting usage patterns from web data. web data provides the information about web user's behavior. Pre-processing of web data is an essential process in web usage mining. This is used to convert the raw data into processed data which is necessary for web mining task. In this research paper, author proposed the effective Pre-processing methodology which involves field extraction, significant attributes selection, data selection, and data cleaning. The efficient proposed methodology improves the quality of web data by managing missing values, noise, inconsistency, and incompleteness which is usually found attached with data. Moreover, obtained results of pre-processing will be further used in frequent pattern discovery.

关键词： web log file web server web usage mining Pre-processing Data cleaning

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web Usage Mining Algorithm for an Academic Search Application

Web Usage Mining Algorithm for an Academic Search Applicatio...

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International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)

作者： Jeyalatha, S. Vijayakumar, B. Manipal Univ Comp Sci Dubai U Arab Emirates BITS Pilani Comp Sci Dubai Campus Dubai U Arab Emirates

ISBN: (纸本)9781728137780

web Usage Mining implies survey of information related to web log file. It can discover the browsing patterns and used for modeling the navigation behavior of web users. Analysis of log file gives an indication of the users' preferences. The data present in the log file cannot be used as it is, for the mining process. The contents of the log file should be preprocessed and put in a structured format. This paper focuses on design and execution of an algorithm for analyzing the web Usage log more specifically for an academic search application. It accepts the web log file and user queries as input and generates output containing the web log details as well as summary data. Descriptive Data Mining is considered for analyzing the web log file. The interestingness measures t-weight and d-weight, are computed. The model discussed in this paper will help significantly in improving user navigation, web design and usage patterns.

关键词： Interestingness Measures log Analysis Preprocessing Structured Data web log file web Usage Mining

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Session identification techniques used in web usage mining A systematic mapping of scholarly literature

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ONLINE INFORMATION REVIEW 2016年第7期40卷 1033-1053页

作者： Fatima, Bahjat Ramzan, Huma Asghar, Sohail COMSATS Inst Informat Technol Dept Comp Sci Islamabad Pakistan

Purpose - The purpose of this paper is to critically analyze the state-of-the-art session identification techniques used in web usage mining (WUM) process in terms of their limitations, features, and methodologies. Design/methodology/approach - In this research, systematic literature review has been conducted using review protocol approach. The methodology consisted of a comprehensive search for relevant literature over the period of 2005-2015, using four online database repositories (i.e. IEEE, Springer, ACM Digital Library, and ScienceDirect). Findings - The findings revealed that this research area is still immature and existing literature lacks the critical review of recent session identification techniques used in WUM process. Originality/value - The contribution of this study is to provide a structured overview of the research developments, to critically review the existing session identification techniques, highlight their limitations and associated challenges and identify areas where further improvements are required so as to complement the performance of existing techniques.

关键词： Clustering Pre-processing Session identification Sessionization web log file web usage mining

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A Unified Model for Preprocessing and Clustering Technique for web Usage Mining

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JOURNAL OF MULTIPLE-VALUED logIC AND SOFT COMPUTING 2016年第3-5期26卷 205-220页

作者： Pandian, P. Senthil Srinivasan, S. Latha Mathavan Engn Coll Dept Informat Technol Madurai Tamil Nadu India Anna Univ Reg Off Dept Comp Sci & Engn Madurai Tamil Nadu India

World Wide web gives huge amount information to the internet user. It is a process of accessing hypertext documents via the internet with a large repository of web pages and links. In that web page images, text, videos and other multimedia are presented and navigate them via hyperlinks. web log file records the information of the user accesses websites. The log file may contain some noisy and ambiguous data which may affect the data mining process. The log file should be Preprocessed to improve the quality of data. User session clustering is implemented in web personalization to understand user activities. Clustering is widely used in data mining and it is the process of grouping of users having similar browsing pattern. This paper presents a detailed discussion about the web log file format, web log file, preprocessing and clustering. Preprocessing consists of data cleaning and data filtering, user identification and session identification. Hidden Data Damage (HDD) algorithm is proposed for data cleaning and data filtering. User and session cluster is carried out to obtain aggregate clustering. Two sets of log files are collected and processed to obtain experimental results.

关键词： web log file web log file format Data Preprocessing Clustering

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Research on data preparation technique in web usage mining

Research on data preparation technique in web usage mining

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International Conference on Information Technology and Industrial Engineering

作者： Liu, Fei Wuhan Inst Technol Comp Sci & Engn Coll Wuhan Peoples R China

Data preparation is important in web usage mining. It introduced the model of web usage mining, the process and related algorithms of data preparation. The experiment shows that the method can identify user sessions a... 详细信息

ISBN: (纸本)9781845648442;9781845648435

关键词： data preparation web usage mining web log file session identification

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Detection and Confirmation of web Robot Requests for Cleaning the Voluminous web log Data

Detection and Confirmation of Web Robot Requests for Cleanin...

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International Conference on IMpact of E-Technology on US (IMPETUS)

作者： Sardar, Tanvir Habib Ansari, Zahid PA Coll Engn Dept Informat Sci & Engn Mangalore Karnataka India PA Coll Engn Dept Comp Sci & Engn Mangalore Karnataka India

ISBN: (纸本)9781479926039

web robots are software applications that run automated tasks over the internet. They traverse the hyperlink structure of the World Wide web so that they can retrieve information. There are many reasons to distinguish web robot requests and user requests. Some tasks of web robots can be harmful to the web. Firstly, web robots are employed for assemble business intelligence at e-commerce sites. In such a state of affairs, the e-commerce site may need to detect robots. Secondly, many e-commerce sites carry out web traffic scrutiny to deduce the way their customers have accessed the site. Unfortunately, such scrutiny can be erroneous by the presence of web robots. Thirdly, web robots often consume considerable network bandwidth and server resources at the expense of other users. A web log file is a web server file automatically created and maintained by a web server to check the activity performed by it. It maintains a history of page requests on its site. In this paper we have used four methods together to detect and finally confirm requests as a robot request. Experiments have been performed on the log file generated from the server of an operational web site named vtulife. com which contains data of march-2013. In our research results of web robot detection using various techniques have been compared and an integrated approach is proposed for the confirmation of the robot request.

关键词： web usage mining web robot detection web log file

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Big Data: Mining of log file through Hadoop

Big Data: Mining of Log File through Hadoop

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International Conference on Human Computer Interactions (ICHCI)

作者： Kotiyal, Bina Kumar, Ankit Pant, Bhaskar Goudar, R. H. GEU Univ Dept Comp Sci Bell Rd Dehra Dun Uttarakhand India GEU Univ Dept Informat Technol Bell Rd Dehra Dun Uttarakhand India

ISBN: (纸本)9781467357029

The unremitting increase of computational strength has produced tremendous flow of data in the past two decades. This tremendous flow of data is known as "big data". Big data is the data which cannot be processed with the aid of existing tools or techniques and if processed can result in interesting information's such as analysing the behaviour of the user, business intelligence etc. This paper discusses the difference between the traditional relational database and big data;it also shows the characteristics of big data. The paper also focuses on the distinct big data channels processes along with the various challenges and as well as on how big data is a solution to the organizations. Big data does not only focus to store and handle the large volume of data but also to analysed and extract the correct information from the data in lesser time span. At last it discusses about hadoop an open source framework that allows the distributed processing for massive datasets on cluster of computers which is shown with using the log file for extraction of information based on user query.

关键词： Big Data web log file Hadoop Hadoop Distributed file System Distributed Processing MapReduce

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Pattern Discovery of web Usage Mining

Pattern Discovery of Web Usage Mining

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International Conference on Computer Technology and Development

作者： Nina, Shahnaz Parvin Rahaman, Md Mahamudur Bhuiyan, Md Khairul Islam Ahmed, Khandakar Entenam Unayes Shahjalal Univ Sci & Technol Sylhet Bangladesh

ISBN: (纸本)9780769538921

This paper provides a comprehensive idea about the pattern discovery of web usage mining. web site designers should have clear understanding of user's profile and site objectives, as well as an emphasized knowledge of the way users will browse web pages. The designers can study the visitor's activities through the web analysis and find patterns of the visitor's behavior. This web analysis involves the transformation and interpretation of the web log records to find out the hidden information or predictive pattern by the data mining and knowledge discovery technique. This result offer a great prospect coupled with the web warehousing.

关键词： web log file web Usage Mining Data Preparation Pattern Discovery Pattern Analysis and Visualization

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Research on User Requirement Knowledge Acquisition By User Access Behavior Analysis

Research on User Requirement Knowledge Acquisition By User A...

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2nd International Conference on Intelligent Computation Technology and Automation

作者： Xiu, HeZhong Shuang, Wang Jun, DuYa Xihua Univ Sch Math & Comp Eng Chengdu 610039 Peoples R China Xihua Univ Sch Mech Engn & Automat Chengdu 610039 Peoples R China

ISBN: (纸本)9780769538044

Obtaining user requirement is a premise of demand-driven product design. By the analysis of several requirements acquisition methods, as well as the change of customer's buying behavior under network conditions, this paper puts forward the methods of user requirement knowledge acquisition by tracking user's browsing behavior. By data purification, user identification and session identification of server log files, the info of user's visits over a period of time in the specific product-related websites is found;the user requirement items are extracted from the visited pages;user requirement values along with the reliability are computed based on the visited numbers of the requirement items. Then, users are divided into user groups to acquire user groups' requirements knowledge. This method can not only help understand users' concerns of existing products' index, but also, to some extent, reflect users' potential demand of the products, which, in turn, can provide enterprises reference for new product development.

关键词： user requirements knowledge acquisition user access behavior web log file

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