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IEEE 23rd International Conference on web Services (ICWS)

作者： Kasi, Sainath Gadhamsetty Tripathi, Samarth Samsung Res & Dev Inst Web Serv Bangalore Karnataka India

ISBN: (纸本)9781509026753

As the World Wide web continues to grow unbounded;users expect intelligent processing and accurate coverage of all its domains. To allow for the same, we present a novel approach to identify and extract key information from web pages with commendable accuracy. We extract important information such as the Title, Main Image, Description, Keywords and FavIcon from a webpage where available, using only the HTML responses without any explicit webpage rendering. The algorithm was modelled to be fast without compromising on its accuracy, is fully automatic, language independent and runs without any human supervision or training. We test our algorithm extensively on over one hundred thousand webpages and successfully extract the key information for 97% of them with an impressive average extraction time of less than 500 milliseconds per webpage.

关键词： web mining web data extraction web Services Mobile web

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Extracting Product Offers from e-Shop websites 11th

Extracting Product Offers from e-Shop Websites

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11th International Conference on web Information Systems and Technologies (webIST)

作者： Horch, Andrea Kett, Holger Weisbecker, Anette Fraunhofer Inst Ind Engn IAO Stuttgart Germany

ISBN: (纸本)9783319309965;9783319309958

On-line retailers as well as e-shoppers are very interested in gathering product records from the web in order to compare products and prices. The consumers compare products and prices to find the best price for a specific product or they want to identify alternatives for a product whereas the on-line retailers need to compare their offers with those of their competitors for being able to remain competitive. As there is a huge number and vast array of product offers in the web the product data needs to be collected through an automated approach. The contribution of this papers is a novel approach for automatically identify and extract product records from arbitrary e-shop websites. The approach extends an existing technique which is called Tag Path Clustering for clustering similar HTML tag paths. The clustering mechanism is combined with a novel filtering mechanism for identifying the product records to be extracted within the websites.

关键词： web data extraction Product record extraction Tag path clustering

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Two Parallel Alignment Algorithms for Big Number of Strings 14

Two Parallel Alignment Algorithms for Big Number of Strings

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International Workshop on Parallel Optimization using/for Multi and Many-Core High Performance Computing (POMCO) in conjunction with 14th International Conference on High Performance Computing and Simulation (HPCS)

作者： Gfrerer, Christine Vajtersic, Marian Kutil, Rade Salzburg Univ Dept Comp Sci A-5020 Salzburg Austria Slovak Acad Sci Dept Informat Bratislava Slovakia

ISBN: (纸本)9781509020881

This poster paper deals with algorithmic solutions for the alignment of a large number of data strings, which is a challenging and computationally demanding task, belonging to the class of NP-hard problems. In order to get practical and time-acceptable solutions, the development of heuristic approaches and the employment of parallelism are inevitable. Two parallel algorithms are presented for solving the alignment problem in the context of extraction of data from web-pages. Both algorithms have their sequential counterpart, which represents an efficient heuristic approach, based on the estimation of local parameters for symbol distances. The algorithms are characterized by different assignments of data to processors of the parallel system: In the first one the processed data sets are distributed according to symbols, in the second one by columns. The algorithms are formulated in pseudocode and implemented with MPI. Their computational and space complexities are estimated and compared. Moreover, they are examined on a parallel cluster with multi-core nodes for a pool of test data coming from web-pages. The results of experiments show that the variant with distribution by columns is less efficient because of high communication costs. The algorithm with the data distribution according to symbols delivers acceptable timings, especially when the matrix of string data is long and thin.

关键词： web data extraction data mining string alignment parallel algorithms MPI

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ViDE: A Vision-Based Approach for Deep web data extraction

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IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2010年第3期22卷 447-460页

作者： Liu, Wei Meng, Xiaofeng Meng, Weiyi Renmin Univ China Sch Informat Beijing 100872 Peoples R China SUNY Binghamton Watson Sch Engn Dept Comp Sci Binghamton NY 13902 USA

Deep web contents are accessed by queries submitted to web databases and the returned data records are enwrapped in dynamically generated web pages (they will be called deep web pages in this paper). Extracting structured data from deep web pages is a challenging problem due to the underlying intricate structures of such pages. Until now, a large number of techniques have been proposed to address this problem, but all of them have inherent limitations because they are web-page-programming-language-dependent. As the popular two-dimensional media, the contents on web pages are always displayed regularly for users to browse. This motivates us to seek a different way for deep web data extraction to overcome the limitations of previous works by utilizing some interesting common visual features on the deep web pages. In this paper, a novel vision-based approach that is web-page-programming-language-independent is proposed. This approach primarily utilizes the visual features on the deep web pages to implement deep web data extraction, including data record extraction and data item extraction. We also propose a new evaluation measure revision to capture the amount of human effort needed to produce perfect extraction. Our experiments on a large set of web databases show that the proposed vision-based approach is highly effective for deep web data extraction.

关键词： web mining web data extraction visual features of deep web pages wrapper generation

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FiVaTech: Page-Level web data extraction from Template Pages

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IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2010年第2期22卷 249-263页

作者： Kayed, Mohammed Chang, Chia-Hui Beni Suef Univ Fac Sci Dept Math Bani Suwayf Egypt Natl Cent Univ Dept Comp Sci & Informat Engn Jhongli 320 Taoyuan Taiwan

web data extraction has been an important part for many web data analysis applications. In this paper, we formulate the data extraction problem as the decoding process of page generation based on structured data and tree templates. We propose an unsupervised, page-level data extraction approach to deduce the schema and templates for each individual Deep website, which contains either singleton or multiple data records in one webpage. FiVaTech applies tree matching, tree alignment, and mining techniques to achieve the challenging task. In experiments, FiVaTech has much higher precision than EXALG and is comparable with other record-level extraction systems like ViPER and MSE. The experiments show an encouraging result for the test pages used in many state-of-the-art web data extraction works.

关键词： Semistructured data web data extraction multiple trees merging wrapper induction

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Implementing web data extraction and Making Mashup with Xtractorz

Implementing Web Data Extraction and Making Mashup with Xtra...

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2nd International Advance Computing Conference

作者： Gultom, Rudy A. G. Sari, Riri Fitri Budiardjo, Bagio Univ Indonesia Dept Elect Engn Depok 16424 Indonesia

ISBN: (纸本)9781424447909

Implementing web data extraction means we can directly extract data from various web pages, where they mostly formed in an unstructured HTML format, into a new structured format such as XML or XHTML. In this paper we review the implementation of web data extraction and stages in making a Mashup. We implement web data extraction by visually extract targeted data from data sources (web pages). Afterward, we combined web data extraction with the stages of making a Mashup, e.g. data retrieval, data source modeling, data cleaning/filtering, data integration and data visualization. Problems arise in querying data sources due to unstructured contents of web pages (HTML), we cannot directly extract data into a new structured form. To address this problem, we propose a system, called Xtractorz, that can perform web data extraction in a Mashup format. We provide a fully visual and interactive user interface with new technique and approach using PHP and AJAX as the programming languages, and MySQL as the data Repository. Furthermore, Xtractorz enables the user to conduct their job without the need to write a script or program or even without any knowledge of computer programming. The test results shows that Xtractorz requires less number of steps in making a Mashup compared with RoboMaker and Karma.

关键词： web data extraction Making Mashup Mashup Stages HTML XML DOM tree PHP AJAX MySQL

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Efficient Emergency Event Tracking Using Features of web data

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CYBERNETICS AND INFORMATION TECHNOLOGIES 2015年第3期15卷 68-87页

作者： Wu, Qunhui Lv, Jianghua Wang, Hao Ma, Shilong Beijing Univ Aeronaut & Astronaut Sch Comp Sci & Engn Beijing 100083 Peoples R China Beijing BoWang China Sci & Technol CO&LTD Beijing 100053 Peoples R China

Huge amount of information has become now available in web services due to their popularity. This web data contains user-contributed information for a variety of emergency events. However, tracking these emergency events is often limited by the lack of efficient tools to analyze the potential events or topics over time, since these events are inherently difficult to predict due to the interference of other unpredictable evolutions. In this paper we propose a two-phase approach, in which we first introduce a novel extraction algorithm to acquire relevant web data and then we utilize a limit theory to determine the periodical convergence time of a specific event, and an event tracking model is constructed using the extracted web data. Based on the significance of multiple features weights and clustering solutions, the interplay between the ordinary events and latent events is discovered to efficiently track the emergency events. Finally, we conduct extensive experiments to verify the effectiveness and efficiency of our approach.

关键词： Emergency event event tracking web data extraction clustering

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web data extraction Based on Structure Feature

Web Data Extraction Based on Structure Feature

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2010 The 3rd International Conference on Computational Intelligence and Industrial Application (PACIIA2010)

作者： Ma Anxiang,Gao Kening,Zhang Xiaohong,Zhang Bin College of Information Science and Engineering Northeastern University Shenyang,China

Most existing methods of web data extraction realize goals based on DOM tree analysis or wrapper building. However,applicability and efficiency of these methods need to be further improved. According to the amount of information,web pages will be divided into two structure types which are 1:1 and 1:N type respectively. As same type of web pages has similar structure features,the paper proposes an approach of two-phase web data extraction base on structure feature. In the phase of samples learning,structure feature and depository rules of web pages are obtained according to the text feature of sample pages. In the phase of information extraction,web data extraction is implemented by matching the page to be extracted with depository rules in knowledge base. Experimental results show that the approach proposed in the paper has well applicability and high efficiency.

关键词： web data extraction structure feature text feature depository rules

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NOVEL COMPLEX EVENT PROCESSING 15

NOVEL COMPLEX EVENT PROCESSING

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International Conference on Advanced Research in Computer Science Engineering and Technology (ICARCSET)

作者： Govindasamy, V Akila, V Hariharan, S. Pandian, R. Suresh Naidu, P. V. Madhu Sudhan Haridev, P. Pondicherry Engn Coll Dept IT & CSE Pondicherry India Pondicherry Engn Coll Pondicherry India

ISBN: (纸本)9781450334419

Complex Event Processing (CEP) is the most favorable platform to build and execute multiple numbers of real-time applications. This paper briefly describes about web data extraction method. It has been implemented on multiple online shopping portals to extract the data in a structured way. Complex Event Processing method has been implemented over the Extracted data to get the requested result as an output for the user. CEP performs an event wise action on extracted data with constant Timestamp between each and every consecutive Events. This system has been named as Complex Event Processing on Extracted data in Online Shopping System (CEP-EDOSS). At the Enterprise level, web data extraction techniques emerge as a key system to perform data analysis in Business and Real Time Business Intelligence process (RTBI). RTBI is the process of delivering information about business operations as they occur. Real time means near to zero latency and access to information whenever it is required. data Latency, Analysis Latency are the parameters used in this paper to measure the extraction of data from multiple sites and Processing time and Response Time are another parameters used in this paper to measure the Event occurrence in our system. From this parameters we conclude that minimum number of time is been taken for a user to obtain a successful output.

关键词： web data extraction web Crawler Complex Event Processing Business Intelligence Publisher-Subscriber

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Development of web Annotation Technique for Search Result Records Using web database 1

Development of Web Annotation Technique for Search Result Re...

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First International Conference on Computing Communication Control and Automation (ICCUBEA)*

作者： Kadam, Sonali T. Bajpai, Sanchika Univ Pune SB Patil Coll Engn Dept Comp Engn Pune Maharashtra India Univ Pune Bhivarabai Sawant Inst Technol & Res Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781479968923

This paper work investigates the needs which web users has to make annotations for their private as well as public use when they access the web pages. web annotation has become an ongoing research issue since the invention of technologies such as HTML, XML, and Wiki. A web annotation is an online annotation that deals with a web page. Semantic web and semantic data is related with integration scenario which defines the metadata construction methods. web database helps to generate query result pages or search result records based on a user's query. A typical result page returned from a web database(WDB) has multiple search result records (SRRs). To get the web extracted records, SRRs to be a machine process able which is frequently useful for deep web data collection, online reading, and online shopping and have meaningful labels. In this paper, we have proposed exploratory automatic annotation techniques by making the use of automatically generated wrappers. Annotation technique firstly forms a group of data units on search result record such that same semantic will be assigned to data of a similar group by using multi-data alignment algorithm. Then we will annotate the every group which will be further aggregated to achieve the ultimate annotation label for the automatic wrapper generation purpose. These wrappers are used to generate annotations for new search result pages of the same database. Experiments will show that our proposed technique is efficient.

关键词： web data extraction web database Label Assignment Wrapping Annotation

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