Web Page Content Research Articles

A Web Mining Approach for Personalized E-Learning System

The Web Mining plays a very important role for the E-learning systems. In personalized E-Learning system, user customize the learning environment based on personal choices. In a general search process ,a hyperlink which is having maximum number of hits will get displayed first . For making a personalized system history of every user need to be saved in the form of user logs. In this paper we present a architecture with the use of Web mining for Web personalization. The proposed system provides a new approach with combination of web usage mining, HITS algorithm and web content mining. It combines hits results on user logs and web page contents with a clustering algorithm called as Lingo clustering algorithm. This proposed system with combined approach gives a better performance than a usage based system. Further the results are computed according to matrices computed from previous and proposed method.

Improvisation in Web Mining Techniques by Scrubbing Log Files

World Wide Web is one of the most interactive and popular medium to spread the information. The increasing popularity and size growth of WWW has overwhelmed with an immense amount of widely dispersed interconnected and dynamic information. Web pages typically contain a large amount of information that is not part of the main content of the pages, e.g. banner ads, navigation bars, copyright notices, etc. Such noise on web pages usually leads to poor results in Web Mining which mainly depends upon the web page content. Therefore, it becomes very essential to extract information from the bulks of data and structure them into useful knowledge that will be helpful for some type of understanding. This leads to the birth of data mining. Web usage mining is the subject field of Web mining which deals with the discovery and analysis of usage patterns from web data specifically web logs in order to improve the web based applications. The Web usage mining process consists of three phases: Data Preprocessing, Pattern Discovery and Pattern Analysis. In this paper an improvised algorithm will be proposed that gives a clean file consisting of only relevant data from the Web usage mining perspective as output. Keywords- Data Mining, Web Mining, Web Usage Mining, Data Pre processing.

Web Algorithms for Information Retrieval

The World Wide Web has emerged to become the biggest and most popular way of communication and information dissemination. Every day, the Web is expending and people generally rely on search engine to explore the web. Because of its rapid and chaotic growth, the resulting network of information lacks of organization and structure. It is a challenge for service provider to provide proper, relevant and quality information to the internet users by using the web page contents and hyperlinks between web pages. This paper deals with analysis and comparison of web pages ranking algorithms based on various parameters to find out their advantages and limitations for ranking web pages and to give the further scope of research in web pages ranking algorithms. Six important algorithms: the Page Rank, Query Dependent-PageRank, HITS, SALSA, Simultaneous Terms Query Dependent-PageRank (SQD-PageRank) and Onto-SQD-PageRank are presented and their performances are discussed.

The Case Study for Human Resource Management Research Based on Web Mining and Semantic Analysis

Extracting information from human resource information by using data mining technology in order that preserve and manage. Through java programming technique, the function of Arachnid that traversing the web page and extract web page content can be realized. Segmentation of content based on the technology of Chinese word segmentation machine of Chinese academy of sciences. Extract human resource information based on key word and save it in MySQL database, using the language of python to program the system of human resource information. The system can provide evidence for government decision-making.

Website Translation and Destination Image Marketing

This study compares the image representations of Reunion Island on the Internet when using original websites in French and their English version. It analyzes the text content of web pages obtained from a list of web information sources providing both French and English versions. Textual data analysis and correspondence analysis based on the most frequent keywords is conducted using the software package Alceste. Results show that the image of Reunion Island is very different between language versions. These differences can be explained by the poor quality of the language translation even though the websites studied were retrieved from the top list of tourism websites providing information on Reunion Island as a destination. This study has strategic implications, as it demonstrates a failure to implement effective and consistent destination marketing by tourism organizations that will confuse the consumer. We make recommendations for future research and practice in terms of improved strategic, tactical, and operational integration.

Healthcare System Based on Semantic Web and XML Technologies

The purpose and the goal of the paper is using a semantic web and XML (the Extensible Markup Language) technologies for managing medical information during a diagnostic process is studied. Following a steady international move towards optimization of health care delivery, the latest development in information technology has drawn the health care industry decision makers’ attention. The introduction of proper information technology innovations within the health care processes should provide the necessary optimization. In this manner can be proposed an approach to manage medical data during the whole diagnostic process using the semantic Web and XML technologies. The purpose of the Semantic Web is to bring structure to the content of Web pages allowing software agents to carry out intelligent tasks for the user. This opens a new set of opportunities that can be utilized to improve health care management on a personal and health care provider level.The aim of this paper in progress is to identify the needs and match them to the services possible with the Semantic Web. In this paper, presented an ontology-based framework that successfully combines both Semantic Web and XML technologies to enable the integrated access to biological data sources. The main goal is the seamless integration and application of these technologies in such a way that their deficiencies are over come and their utility maximized.Keywords: Health Care, Semantic Web, Ontology, XML.

Adapted Web Crawler for Mining Offline Web Data using AFHC

focused hyperlink crawler (AFHC) aim to search the entire inner level sub link of the web pages related to a specific topic and to download unique web pages to local disk. The download web page information searched in offline browsing and avoids the repeated searches in the web server to give a solution to problem. The major problem is to retrieve the maximal set of relevant and quality pages. Crawler software can be retrieve web pages by hyperlinks through internet. The number of web sites using web crawlers cannot retrieve the relevant pages. The system have browser and search engine. Browser using AFHC reduce time to finding accurate content in web pages in the hyperlinks and also restrict to download web pages to local disk. Search engine using extended cocitaion algorithm to retrieve accurate content in the local disk and search based on any word, all word and phrase matching in the local disk. It is useful to the student and organization. The research is easily found to personalize the crawl history and search history for knowing the user transactions.

A neurology-inspired model of web usage

The problem of predicting human behavior has been a great challenge for several disciplines including computer science. In particular, web user browsing behavior has been studied from the machine learning point of view, a field that has been coined web usage mining (WUM). However, current WUM techniques can be negatively impacted by changes in web site structure and content (e.g. Web 2.0). The key reason behind this issue may be that machine learning algorithms learn the observed behavior according to a particular training set, but do not model the user behavior under different conditions. We propose a simulation model that mimics human interaction with the web by recovering observed navigational steps. This web usage model is inspired by a neurophysiology's stochastic description of decision making and by the information utility of web page content. The proposed model corresponds to a high-dimensional stochastic process based on the leaky competing accumulator (LCA) neural model. We solve high-dimensional issues by considering a mesh-less symbolic interpolation. As a proof-of-concept we test the web user simulation system on an academic web site by recovering most of the observed behavior (73%). Therefore, our approach operationally describes web users that seem to react as observed users confronted by changes in the web site interface.

Semantic contextual advertising based on the open directory project

Contextual advertising seeks to place relevant textual ads within the content of generic webpages. In this article, we explore a novel semantic approach to contextual advertising. This consists of three tasks: (1) building a well-organized hierarchical taxonomy of topics, (2) developing a robust classifier for effectively finding the topics of pages and ads, and (3) ranking ads based on the topical relevance to pages. First, we heuristically build our own taxonomy of topics from the Open Directory Project (ODP). Second, we investigate how to increase classification accuracy by taking the unique characteristics of the ODP into account. Last, we measure the topical relevance of ads by applying a link analysis technique to the similarity graph carefully derived from our taxonomy. Experiments show that our classification method improves the performance of Ma- F 1 by as much as 25.7% over the baseline classifier. In addition, our ranking method enhances the relevance of ads substantially, up to 10% in terms of precision at k , compared to a representative strategy.

A hybrid approach for content extraction with text density and visual importance of DOM nodes

Additional contents in web pages, such as navigation panels, advertisements, copyrights and disclaimer notices, are typically not related to the main subject and may hamper the performance of Web data mining. They are traditionally taken as noises and need to be removed properly. To achieve this, two intuitive and crucial kinds of information--the textual information and the visual information of web pages--is considered in this paper. Accordingly, Text Density and Visual Importance are defined for the Document Object Model (DOM) nodes of a web page. Furthermore, a content extraction method with these measured values is proposed. It is a fast, accurate and general method for extracting content from diverse web pages. And with the employment of DOM nodes, the original structure of the web page can be preserved. Evaluated with the CleanEval benchmark and with randomly selected pages from well-known Web sites, where various web domains and styles are tested, the effect of the method is demonstrated. The average F1-scores with our method were 8.7 % higher than the best scores among several alternative methods.

A Study on Content Production According to Change of Advertisement Types Used in Web Pages and SNS(Social Networking Service)

본 연구에서는 웹페이지와 SNS(Social Networking Service)에서 사용되고 있는 광고 콘텐츠 유형 변화에 대해서 연구하였다.BR 인터넷 광고는 광고, 구매, 결제, 배송, 홍보 및 사후관리 등 마케팅 전 과정을 인터넷으로 관리한다. 인터넷 광고와 모바일 다채널화의 광고 효과는 다른 매체광고 보다 광고 효과가 높고, 계속하여 증가 하고 있다. 인터넷 광고의 장점은 광고 제작과 수정이 타 광고 매체에 비해서 수월하고, 신속한 광고 의사를 결정하는데 도움이 되고, 다른 광고 매체에 비해 상대적으로 비용이 저렴하다. 또한 타겟 광고를 할 수 있고, 원하는 시간과 장시간 광고를 할 수 있고, 반복 시청과 다양한 멀티미디어 광고 제작을 통하여 흥미와 관심을 갖게 한다. 또한 인터넷 광고의 효과로서 사용자가 직접 참여하는 양방향성 광고 효과를 갖고 있다. 인터넷 광고는 기업의 수익모델에 커다란 영향을 미친다. 이러한 인터넷 광고를 웹페이지에서 콘텐츠로 제작하는데 광고의 유형과 특성, 그리고 광고 시간, 광고 콘텐츠의 사이즈가 고려되어야 한다. 또한 웹 광고인 경우 웹 페이지의 위치와 시간과 크기에 따라 콘텐츠 제작이 달라진다. 웹에서의 광고 콘텐츠 제작은 컴퓨터 그래픽 기술로서 광고 콘텐츠 유형 변화에 관계가 높다.BR 초기의 광고 콘텐츠는 텍스트 기술을 사용하여 타이포 그래픽과 애니메이션 기술을 적용하였고, 그 이후 상호작용 기술인 인터랙티브 기법을 적용하여 플래시애니메이션 기법을 적용하여 광고 콘텐츠를 제작하였다. 그 이후 웹 2.0 시대에서는 동영상 콘텐츠가 광고제작 기술로 적용되었고, 3차원 그래픽 기술과 모션그래픽 기술이 적용되면서 광고 콘텐츠에 다양한 비디오 효과를 나타내게 되었다. 따라서 광고 콘텐츠 제작이 보다 창조적인 예술의 분야로 발전하면서 광고 콘텐츠는 광고 효과에 극대화를 갖게 되었다.BR 최근 스마트 폰의 등장과 함께 다양한 모바일 단말기들이 보급됨으로 SNS(Social Networking Service)가 활성화 되면서 정보의 홍수를 이루게 되었고, 빅데이터 시대를 맞이하게 되었다. 이러한 정보의 증가와 함께 홍보 및 광고에 보다 정보를 최소화 하면서 효과를 나타낼 수 있는 대안으로 인포그래픽이 적용되었다. SNS(Social Networking Service)에서 다양한 홍보 및 광고를 위하여 인포그래픽으로 콘텐츠를 제작한다.BR 따라서 본 연구에서는 웹페이지에서 SNS에 이르기까지 광고 콘텐츠의 유형 변화를 나타내었고, 이러한 광고 콘텐츠 유형 변화는 광고 효과를 보다 더 잘 나타내기 위해 인터랙티브 그래픽, 모션그래픽, 인포그래픽을 사용하여 광고 효과를 나타낸 것이다. 따라서 본 연구에서는 광고 콘텐츠 제작에 적용되는 인터랙티브 콘텐츠 제작기술과 모션그래픽 제작 기술, 인포그래픽 제작기술을 광고의 특성과 유형에 따라 효율성이 있음을 나타내었다. 이러한 컴퓨터 그래픽 기술들을 적용함으로 광고 콘텐츠 제작을 잘 적용하여 인간의 삶의 질을 높이고, 광고 유형 변화에 잘 적용되기를 바란다. 또한 기업 홍보와 제품 홍보를 잘 반영하여 보다 아름다운 세상, 행복한 세상으로 광고 콘텐츠가 만들어 지고, 사용되길 바란다.

Health Care System Based on Semantic Web and XML Technologies

The purpose and the goal of the paper is using a semantic web and XML (the Extensible Markup Language) technologies for managing medical information during a diagnostic process is studied. Following a steady international move towards optimization of health care delivery, the latest development in information technology has drawn the health care industry decision makers’ attention. The introduction of proper information technology innovations within the health care processes should provide the necessary optimization. In this manner can be proposed an approach to manage medical data during the whole diagnostic process using the semantic Web and XML technologies. The purpose of the Semantic Web is to bring structure to the content of Web pages allowing software agents to carry out intelligent tasks for the user. This opens a new set of opportunities that can be utilized to improve health care management on a personal and health care provider level. The aim of this paper in progress is to identify the needs and match them to the services possible with the Semantic Web. In this paper, presented an ontology-based framework that successfully combines both Semantic Web and XML technologies to enable the integrated access to biological data sources. The main goal is the seamless integration and application of these technologies in such a way that their deficiencies are over come and their utility maximized. Keywords : Health Care, Semantic Web, Ontology, XML

Detecting Cloaking Web Spam Using Hash Function

Web spam is an attempt to boost the ranking of special pages in search engine results. Cloaking is a kind of spamming technique. Previous cloaking detection methods based on terms/links differences between crawler and browser's copies are not accurate enough. The latest technique is tag-based method. This method could find cloaked pages better than previous algorithms. However, addressing the content of web pages provides more accurate results. This paper proposes an algorithm, working based on term differences between crawler and browser's copies. In addition, dynamic cloaking, which is a new and complicated kind of cloaking, is addressed. In order to increase the speed of comparison, we introduce hash value, calculated by Hash Function. The proposed algorithm has been tested with a data set of URLs. Experimental results indicate that our algorithm outperforms previous methods in both precision and recall. We estimate that about 9% of all URLs in data set utilize static cloaking and about 2% of all URLs utilize dynamic cloaking.

Crawling Microblog by Common-Designed Software

A mount of data of microblogs is needed to be crawled for research, business analyzing, and so on. However, a lot of dynamic Web techniques are used in microblog Web pages. That makes it hard to crawl data by parsing the contents of Web pages for traditional Web page crawlers. Fortunately, microblogs provide APIs. Well-structured data can be returned to users simply by accessing those APIs in form of URLs. Basing on that mechanism, researchers have obtained some data from microblogs to research. Nevertheless, no common software for crawling microblog has been published up to now. Everyone has to start designing a microblog crawler from very beginning. A common software architecture based on microblog APIs for microblog crawler is proposed in this paper, which is named as MBCrawler. Its structure, architecture, and key classes are introduced. It can be seen that MBCrawler is modular and scalable. By implementing a real microblog crawler for Sina Weibo, it is shown that MBCrawler can fit specific features of different microblogs. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2805 Full Text: PDF

Open source column

Multimedia analysis is an exciting and fast-moving research area. Unfortunately, historically there has been a lack of software solutions in a common programming language for performing scalable integrated analysis of all modalities of media (images, videos, audio, text, web-pages, etc). For example, in the image analysis world, OpenCV and Matlab are commonly used by researchers, whilst many common Natural Language Processing tools are built using Java. The lack of coherency between these tools and languages means that it is often difficult to research and develop rational, comprehensible and repeatable software implementations of algorithms for performing multimodal multimedia analysis. These problems are also exacerbated by the lack of any principled software engineering (separation of concerns, minimised code repetition, maintainability, understandability, premature optimisation and over optimisation) often found in research code. OpenIMAJ is a set of libraries and tools for multimedia content analysis and content generation that aims to fill this gap and address the concerns. OpenIMAJ provides a coherent interface to a very broad range of techniques, and contains everything from stateof- the-art computer vision (e.g. SIFT descriptors, salient region detection, face detection and description, etc.) and advanced data clustering and hashing, through to software that performs analysis on the content, layout and structure of webpages. A full list of the all the modules and an overview of their functionalities for the latest OpenIMAJ release can be found here. OpenIMAJ is primarily written in Java and, as such is completely platform independent. The video-capture and hardware libraries contain some native code but Linux, OSX and Windows are supported out of the box (under both 32 and 64 bit JVMs; ARM processors are also supported under Linux). It is possible to write programs that use the libraries in any JVM language that supports Java interoperability, for example Groovy and Scala. OpenIMAJ can even be run on Android phones and tablets. As it's written using Java, you can run any application built using OpenIMAJ on any of the supported platforms without even having to recompile the code.

Research on Extracting Main Content of Webpage Based on Text Density and Link Density

Research on Extracting Main Content of Webpage Based on Text Density and Link Density

A Semi-Supervised Learning Method for Product Named Entity Recognition

A semi-supervised approach based on a three-level framework for product named entity recognition is presented.The structure features and relationships among different parts of product named entities are studied,and a combined method is applied.A hidden conditional random field model is built so as to utilize the hidden status of learned samples.The labels failed to be learned by the bootstrapping algorithm is considered as hidden statuses.Experiment in digital camera area shows that,with only a few manually labeled data,this method could recognize product named entities from text contents of web pages very well.

A Grammatical Evolution Approach for Content Extraction of Electronic Commerce Website

Web content extraction, a problem of identifying and extracting interesting information from Web pages, plays an important role in integrating data from different sources for advanced information-based services. In this paper, an approach and techniques of extracting electronic commercial information from the Web pages without any given template is investigated in a way of Grammatical Evolution (GE) method. Although a lot of research used the Xpath technique to extract the content of Web pages, but due to the complexity of the Xpath grammar, it is too difficult to perform the processing automatically for evolutional tools. Hence, a reduced language integrating Xpath and DOM techniques is given to generate the solution of parse in a BNF grammar form, which is used in the GE. Moreover, a fitness function evaluation method is also proposed on the fuzzy membership of the two parts in the chromosome. Finally, empirical results on several real Web pages show that the new proposed technique can segment data records and extract data from them accurately, automatically and flexibly.

A robust zero-watermarking algorithm for copyright protection of text documents

The widespread use of Internet and other communication technologies has brought about ease in reproducing, disclosing and distributing digital content. In addition to getting the benefits of information exchange, the digital community is confronted with authentication, forgery and copyright protection issues. Text is the most frequently used medium travelling over the Internet, along with images, audio and video. Majority of the content of books, newspapers, web pages, advertisements, research papers, legal documents and many other documents is basically, plain text. Therefore, copyright protection of plain text is a most important issue. In this article, we propose a robust zero-watermarking algorithm based on prepositions and double letters for copyright protection of plain text. The embedding algorithm uses occurrences of prepositions and double letters in the text to generate a key based on watermark. The extraction algorithm extracts the watermark from the noisy text to identify the original owner. Experimental results illustrate the effectiveness of the proposed algorithm on text encountering combined insertion, deletion and re-ordering attacks, both in the dispersed and localized forms. The results are also compared to a recent work on text watermarking.

State of Art: Semantic Web

Semantic Web is an extension to the current web. It will convert the way we use World Wide Web (WWW) by giving the machine the capability to process and infer data in web. It starts as a vision and becomes a future trend in web. Due to the huge data that is scattered as web pages in web today, adding semantic meaning to data stored in these pages became necessary for the next age of information technology. The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users. Several tools and new technologies have been emerged to help bring this vision to reality. In this paper, Semantic Web is defined and described with its layering architecture and supporting technologies and tools. An example is given to show how to use these tools to semantically representing data model. At last, challenges and difficulties faced building this web and made it an extension to the current web has been discussed.