To improve question answering （QA） performance based on real-world web data sets,a new set of question classes and a general answer re-ranking model are defined.With pre-defined dictionary and grammatical analysis,t...To improve question answering （QA） performance based on real-world web data sets,a new set of question classes and a general answer re-ranking model are defined.With pre-defined dictionary and grammatical analysis,the question classifier draws both semantic and grammatical information into information retrieval and machine learning methods in the form of various training features,including the question word,the main verb of the question,the dependency structure,the position of the main auxiliary verb,the main noun of the question,the top hypernym of the main noun,etc.Then the QA query results are re-ranked by question class information.Experiments show that the questions in real-world web data sets can be accurately classified by the classifier,and the QA results after re-ranking can be obviously improved.It is proved that with both semantic and grammatical information,applications such as QA, built upon real-world web data sets, can be improved,thus showing better performance.展开更多
With the rapid development of Web, there are more and more Web databases available for users to access. At the same time, job searchers often have difficulties in first finding the right sources and then querying over...With the rapid development of Web, there are more and more Web databases available for users to access. At the same time, job searchers often have difficulties in first finding the right sources and then querying over them, providing such an integrated job search system over Web databases has become a Web application in high demand. Based on such consideration, we build a deep Web data integration system that supports unified access for users to multiple job Web sites as a job meta-search engine. In this paper, the architecture of the system is given first, and the key components in the system are introduced.展开更多
This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube const...This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube construction is proposed, which includes Web data modeling based on MIX （ Metadam based Integration model for data X-change ）, generic and specific mapping rules design, and a transformation algorithm for mapping Web data to a multidimensional array. Besides, the structure and implementation of the prototype of a Web data base cube are discussed.展开更多
In this paper, we propose a flexible locationbased service （LBS） middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge d...In this paper, we propose a flexible locationbased service （LBS） middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge data source of location relative information, we integrate the common used web data extraction techniques into the middleware framework, exposing a unified web data interface for the upper applications to make them more attractive. Besides, the framework also emphasizes some common LBS issues, including positioning, location modeling, location-dependent query processing, privacy and secure management.展开更多
This paper investigates the Web data aggregation issues in multidimensional on-line analytical processing （MOLAP） and presents a rule-driven aggregation approach. The core of the approach is defining aggregate rules...This paper investigates the Web data aggregation issues in multidimensional on-line analytical processing （MOLAP） and presents a rule-driven aggregation approach. The core of the approach is defining aggregate rules. To define the rules for reading warehouse data and computing aggregates, a rule definition language - array aggregation language （AAL） is developed. This language treats an array as a function from indexes to values and provides syntax and semantics based on monads. External functions can be called in aggregation rules to specify array reading, writing, and aggregating. Based on the features of AAL, array operations are unified as function operations, which can be easily expressed and automatically evaluated. To implement the aggregation approach, a processor for computing aggregates over the base cube and for materializing them in the data warehouse is built, and the component structure and working principle of the aggregation processor are introduced.展开更多
A vision based query interface annotation meth od is used to relate attributes and form elements in form based web query interfaces, this method can reach accuracy of 82%. And a user participation method is used to tu...A vision based query interface annotation meth od is used to relate attributes and form elements in form based web query interfaces, this method can reach accuracy of 82%. And a user participation method is used to tune the result; user can answer ＂yes＂ or ＂no＂ for existing annotations, or manually annotate form elements. Mass feedback is added to the annotation algorithm to produce more accurate result. By this approach, query interface annotation can reach a perfect accuracy.展开更多
采用Web data mining对远程教育进行分析,根据受教育对象存在的个体差异,提出个性化远程学习系统的框架结构思想和个性化服务的理念,对相关信息进行数据挖掘并建立起一个集智能化、个性化为一体的远程教育系统,从而更好地改善远程教育...采用Web data mining对远程教育进行分析,根据受教育对象存在的个体差异,提出个性化远程学习系统的框架结构思想和个性化服务的理念,对相关信息进行数据挖掘并建立起一个集智能化、个性化为一体的远程教育系统,从而更好地改善远程教育服务的现状。展开更多
Web data extraction is to obtain valuable data from the tremendous information resource of the World Wide Web according to the pre - defined pattern. It processes and classifies the data on the Web. Formalization of t...Web data extraction is to obtain valuable data from the tremendous information resource of the World Wide Web according to the pre - defined pattern. It processes and classifies the data on the Web. Formalization of the procedure of Web data extraction is presented, as well as the description of crawling and extraction algorithm. Based on the formalization, an XML - based page structure description language, TIDL, is brought out, including the object model, the HTML object reference model and definition of tags. At the final part, a Web data gathering and querying application based on Internet agent technology, named Web Integration Services Kit (WISK) is mentioned.展开更多
Extracting and mining social networks information from massive Web data is of both theoretical and practical significance. However, one of definite features of this task was a large scale data processing, which remain...Extracting and mining social networks information from massive Web data is of both theoretical and practical significance. However, one of definite features of this task was a large scale data processing, which remained to be a great challenge that would be addressed. MapReduce is a kind of distributed programming model. Just through the implementation of map and reduce those two functions, the distributed tasks can work well. Nevertheless, this model does not directly support heterogeneous datasets processing, while heterogeneous datasets are common in Web. This article proposes a new framework which improves original MapReduce framework into a new one called Map-Reduce-Merge. It adds merge phase that can efficiently solve the problems of heterogeneous data processing. At the same time, some works of optimization and improvement are done based on the features of Web data.展开更多
The World Wide Web provides a wealth of information about everything, including contemporary audio and visual art events, which are discussed on media outlets, blogs, and specialized websites alike. This information m...The World Wide Web provides a wealth of information about everything, including contemporary audio and visual art events, which are discussed on media outlets, blogs, and specialized websites alike. This information may become a robust source of real-world data, which may form the basis of an objective data-driven analysis. In this study, a methodology for collecting information about audio and visual art events in an automated manner from a large array of websites is presented in detail. This process uses cutting edge Semantic Web, Web Search and Generative AI technologies to convert website documents into a collection of structured data. The value of the methodology is demonstrated by creating a large dataset concerning audiovisual events in Greece. The collected information includes event characteristics, estimated metrics based on their text descriptions, outreach metrics based on the media that reported them, and a multi-layered classification of these events based on their type, subjects and methods used. This dataset is openly provided to the general and academic public through a Web application. Moreover, each event’s outreach is evaluated using these quantitative metrics, the results are analyzed with an emphasis on classification popularity and useful conclusions are drawn concerning the importance of artistic subjects, methods, and media.展开更多
Data are crucial to the growth of e-commerce in today's world of highly demanding hyper-personalized consumer experiences,which are collected using advanced web scraping technologies.However,core data extraction e...Data are crucial to the growth of e-commerce in today's world of highly demanding hyper-personalized consumer experiences,which are collected using advanced web scraping technologies.However,core data extraction engines fail because they cannot adapt to the dynamic changes in website content.This study investigates an intelligent and adaptive web data extraction system with convolutional and Long Short-Term Memory(LSTM)networks to enable automated web page detection using the You only look once(Yolo)algorithm and Tesseract LSTM to extract product details,which are detected as images from web pages.This state-of-the-art system does not need a core data extraction engine,and thus can adapt to dynamic changes in website layout.Experiments conducted on real-world retail cases demonstrate an image detection(precision)and character extraction accuracy(precision)of 97%and 99%,respectively.In addition,a mean average precision of 74%,with an input dataset of 45 objects or images,is obtained.展开更多
How to integrate heterogeneous semi-structured Web records into relational database is an important and challengeable research topic. An improved model of conditional random fields was presented to combine the learnin...How to integrate heterogeneous semi-structured Web records into relational database is an important and challengeable research topic. An improved model of conditional random fields was presented to combine the learning of labeled samples and unlabeled database records in order to reduce the dependence on tediously hand-labeled training data. The pro- posed model was used to solve the problem of schema matching between data source schema and database schema. Experimental results using a large number of Web pages from diverse domains show the novel approach＇s effectiveness.展开更多
We propose a three-step technique to achieve this purpose. First, we utilize a collection of XML namespaces organized into hierarchical structure as a medium for expressing data semantics. Second, we define the format...We propose a three-step technique to achieve this purpose. First, we utilize a collection of XML namespaces organized into hierarchical structure as a medium for expressing data semantics. Second, we define the format of resource descriptor for the information source discovery scheme so that we can dynamically register and/or deregister the Web data sources on the fly. Third, we employ an inverted-index mechanism to identify the subset of information sources that are relevant to a particular user query. We describe the design, architecture, and implementation of our approach—IWDS, and illustrate its use through case examples. Key words integration - heterogeneity - Web data source - XML namespace CLC number TP 311.13 Foundation item: Supported by the National Key Technologies R&D Program of China(2002BA103A04)Biography: WU Wei (1975-), male, Ph.D candidate, research direction: information integration, distribute computing展开更多
A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular product.Websites are designed for human underst...A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular product.Websites are designed for human understanding and not for machines.Therefore,to make data machine-readable,it requires techniques to grab data from web pages.Researchers have addressed the problem using two approaches,i.e.,knowledge engineering and machine learning.State of the art knowledge engineering approaches use the structure of documents,visual cues,clustering of attributes of data records and text processing techniques to identify data records on a web page.Machine learning approaches use annotated pages to learn rules.These rules are used to extract data from unseen web pages.The structure of web documents is continuously evolving.Therefore,new techniques are needed to handle the emerging requirements of web data extraction.In this paper,we have presented a novel,simple and efficient technique to extract data from web pages using visual styles and structure of documents.The proposed technique detects Rich Data Region(RDR)using query and correlative words of the query.RDR is then divided into data records using style similarity.Noisy elements are removed using a Common Tag Sequence(CTS)and formatting entropy.The system is implemented using JAVA and runs on the dataset of real-world working websites.The effectiveness of results is evaluated using precision,recall,and F-measure and compared with five existing systems.A comparison of the proposed technique to existing systems has shown encouraging results.展开更多
The massive web-based information resources have led to an increasing demand for effective automatic retrieval of target information for web applications. This paper introduces a web-based data extraction tool that de...The massive web-based information resources have led to an increasing demand for effective automatic retrieval of target information for web applications. This paper introduces a web-based data extraction tool that deploys various algorithms to locate, extract and filter tabular data from HTML pages and to transform them into new web-based representations. The tool has been applied in an aquaculture web application platform for extracting and generating aquatic product market information. Results prove that this tool is very effective in extracting the required data from web pages.展开更多
To extract structured data from a web page with customized requirements,a user labels some DOM elements on the page with attribute names.The common features of the labeled elements are utilized to guide the user throu...To extract structured data from a web page with customized requirements,a user labels some DOM elements on the page with attribute names.The common features of the labeled elements are utilized to guide the user through the labeling process to minimize user efforts,and are also utilized to retrieve attribute values.To turn the attribute values into a structured result,the attribute pattern needs to be induced.For this purpose,a space-optimized suffix tree called attribute tree is built to transform the document object model(DOM) tree into a simpler form while preserving its useful properties such as attribute sequence order.The pattern is induced bottom-up on the attribute tree,and is further used to build the structured result.Experiments are conducted and show high performance of our approach in terms of precision,recall and structural correctness.展开更多
基金Microsoft Research Asia Internet Services in Academic Research Fund(No.FY07-RES-OPP-116)the Science and Technology Development Program of Tianjin(No.06YFGZGX05900)
文摘To improve question answering （QA） performance based on real-world web data sets,a new set of question classes and a general answer re-ranking model are defined.With pre-defined dictionary and grammatical analysis,the question classifier draws both semantic and grammatical information into information retrieval and machine learning methods in the form of various training features,including the question word,the main verb of the question,the dependency structure,the position of the main auxiliary verb,the main noun of the question,the top hypernym of the main noun,etc.Then the QA query results are re-ranked by question class information.Experiments show that the questions in real-world web data sets can be accurately classified by the classifier,and the QA results after re-ranking can be obviously improved.It is proved that with both semantic and grammatical information,applications such as QA, built upon real-world web data sets, can be improved,thus showing better performance.
基金Supportted by the Natural Science Foundation ofChina (60573091 ,60273018) National Basic Research and Develop-ment Programof China (2003CB317000) the Key Project of Minis-try of Education of China (03044) .
文摘With the rapid development of Web, there are more and more Web databases available for users to access. At the same time, job searchers often have difficulties in first finding the right sources and then querying over them, providing such an integrated job search system over Web databases has become a Web application in high demand. Based on such consideration, we build a deep Web data integration system that supports unified access for users to multiple job Web sites as a job meta-search engine. In this paper, the architecture of the system is given first, and the key components in the system are introduced.
基金The National Natural Science Foundation of China (No.60573165)
文摘This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube construction is proposed, which includes Web data modeling based on MIX （ Metadam based Integration model for data X-change ）, generic and specific mapping rules design, and a transformation algorithm for mapping Web data to a multidimensional array. Besides, the structure and implementation of the prototype of a Web data base cube are discussed.
基金Supported by the National Natural Science Foun-dation of China (60573091 ,60273018)National Basic Research andDevelopment Programof China(2003CB317000) +1 种基金the Key Project ofMinistry of Education of China (03044) Programfor NewCentu-ry Excellent Talents in University(NCET) .
文摘In this paper, we propose a flexible locationbased service （LBS） middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge data source of location relative information, we integrate the common used web data extraction techniques into the middleware framework, exposing a unified web data interface for the upper applications to make them more attractive. Besides, the framework also emphasizes some common LBS issues, including positioning, location modeling, location-dependent query processing, privacy and secure management.
基金The National Natural Science Foundationof China (No60573165)
文摘This paper investigates the Web data aggregation issues in multidimensional on-line analytical processing （MOLAP） and presents a rule-driven aggregation approach. The core of the approach is defining aggregate rules. To define the rules for reading warehouse data and computing aggregates, a rule definition language - array aggregation language （AAL） is developed. This language treats an array as a function from indexes to values and provides syntax and semantics based on monads. External functions can be called in aggregation rules to specify array reading, writing, and aggregating. Based on the features of AAL, array operations are unified as function operations, which can be easily expressed and automatically evaluated. To implement the aggregation approach, a processor for computing aggregates over the base cube and for materializing them in the data warehouse is built, and the component structure and working principle of the aggregation processor are introduced.
基金Supported by the National Natural Science Foun-dation of China (60573091 ,60273018)
文摘A vision based query interface annotation meth od is used to relate attributes and form elements in form based web query interfaces, this method can reach accuracy of 82%. And a user participation method is used to tune the result; user can answer ＂yes＂ or ＂no＂ for existing annotations, or manually annotate form elements. Mass feedback is added to the annotation algorithm to produce more accurate result. By this approach, query interface annotation can reach a perfect accuracy.
基金Note:Contents discussed in this paper are part of a key project,No.2000-A31-01-04,sponsored by Ministry of Science and Technology of P.R.China
文摘Web data extraction is to obtain valuable data from the tremendous information resource of the World Wide Web according to the pre - defined pattern. It processes and classifies the data on the Web. Formalization of the procedure of Web data extraction is presented, as well as the description of crawling and extraction algorithm. Based on the formalization, an XML - based page structure description language, TIDL, is brought out, including the object model, the HTML object reference model and definition of tags. At the final part, a Web data gathering and querying application based on Internet agent technology, named Web Integration Services Kit (WISK) is mentioned.
文摘Extracting and mining social networks information from massive Web data is of both theoretical and practical significance. However, one of definite features of this task was a large scale data processing, which remained to be a great challenge that would be addressed. MapReduce is a kind of distributed programming model. Just through the implementation of map and reduce those two functions, the distributed tasks can work well. Nevertheless, this model does not directly support heterogeneous datasets processing, while heterogeneous datasets are common in Web. This article proposes a new framework which improves original MapReduce framework into a new one called Map-Reduce-Merge. It adds merge phase that can efficiently solve the problems of heterogeneous data processing. At the same time, some works of optimization and improvement are done based on the features of Web data.
文摘The World Wide Web provides a wealth of information about everything, including contemporary audio and visual art events, which are discussed on media outlets, blogs, and specialized websites alike. This information may become a robust source of real-world data, which may form the basis of an objective data-driven analysis. In this study, a methodology for collecting information about audio and visual art events in an automated manner from a large array of websites is presented in detail. This process uses cutting edge Semantic Web, Web Search and Generative AI technologies to convert website documents into a collection of structured data. The value of the methodology is demonstrated by creating a large dataset concerning audiovisual events in Greece. The collected information includes event characteristics, estimated metrics based on their text descriptions, outreach metrics based on the media that reported them, and a multi-layered classification of these events based on their type, subjects and methods used. This dataset is openly provided to the general and academic public through a Web application. Moreover, each event’s outreach is evaluated using these quantitative metrics, the results are analyzed with an emphasis on classification popularity and useful conclusions are drawn concerning the importance of artistic subjects, methods, and media.
文摘Data are crucial to the growth of e-commerce in today's world of highly demanding hyper-personalized consumer experiences,which are collected using advanced web scraping technologies.However,core data extraction engines fail because they cannot adapt to the dynamic changes in website content.This study investigates an intelligent and adaptive web data extraction system with convolutional and Long Short-Term Memory(LSTM)networks to enable automated web page detection using the You only look once(Yolo)algorithm and Tesseract LSTM to extract product details,which are detected as images from web pages.This state-of-the-art system does not need a core data extraction engine,and thus can adapt to dynamic changes in website layout.Experiments conducted on real-world retail cases demonstrate an image detection(precision)and character extraction accuracy(precision)of 97%and 99%,respectively.In addition,a mean average precision of 74%,with an input dataset of 45 objects or images,is obtained.
基金Supported by the National Defense Pre-ResearchFoundation of China(4110105018)
文摘How to integrate heterogeneous semi-structured Web records into relational database is an important and challengeable research topic. An improved model of conditional random fields was presented to combine the learning of labeled samples and unlabeled database records in order to reduce the dependence on tediously hand-labeled training data. The pro- posed model was used to solve the problem of schema matching between data source schema and database schema. Experimental results using a large number of Web pages from diverse domains show the novel approach＇s effectiveness.
文摘We propose a three-step technique to achieve this purpose. First, we utilize a collection of XML namespaces organized into hierarchical structure as a medium for expressing data semantics. Second, we define the format of resource descriptor for the information source discovery scheme so that we can dynamically register and/or deregister the Web data sources on the fly. Third, we employ an inverted-index mechanism to identify the subset of information sources that are relevant to a particular user query. We describe the design, architecture, and implementation of our approach—IWDS, and illustrate its use through case examples. Key words integration - heterogeneity - Web data source - XML namespace CLC number TP 311.13 Foundation item: Supported by the National Key Technologies R&D Program of China(2002BA103A04)Biography: WU Wei (1975-), male, Ph.D candidate, research direction: information integration, distribute computing
文摘A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular product.Websites are designed for human understanding and not for machines.Therefore,to make data machine-readable,it requires techniques to grab data from web pages.Researchers have addressed the problem using two approaches,i.e.,knowledge engineering and machine learning.State of the art knowledge engineering approaches use the structure of documents,visual cues,clustering of attributes of data records and text processing techniques to identify data records on a web page.Machine learning approaches use annotated pages to learn rules.These rules are used to extract data from unseen web pages.The structure of web documents is continuously evolving.Therefore,new techniques are needed to handle the emerging requirements of web data extraction.In this paper,we have presented a novel,simple and efficient technique to extract data from web pages using visual styles and structure of documents.The proposed technique detects Rich Data Region(RDR)using query and correlative words of the query.RDR is then divided into data records using style similarity.Noisy elements are removed using a Common Tag Sequence(CTS)and formatting entropy.The system is implemented using JAVA and runs on the dataset of real-world working websites.The effectiveness of results is evaluated using precision,recall,and F-measure and compared with five existing systems.A comparison of the proposed technique to existing systems has shown encouraging results.
基金Supported by the Shanghai Education Committee (No.06KZ016)
文摘The massive web-based information resources have led to an increasing demand for effective automatic retrieval of target information for web applications. This paper introduces a web-based data extraction tool that deploys various algorithms to locate, extract and filter tabular data from HTML pages and to transform them into new web-based representations. The tool has been applied in an aquaculture web application platform for extracting and generating aquatic product market information. Results prove that this tool is very effective in extracting the required data from web pages.
基金Supported by the National High Technology Research and Development Programme of China(No.2009AA01 Z141)the National Natural Science Foundation of China(No.60573117)Beijing Natural Science Foundation(No.4131001)
文摘To extract structured data from a web page with customized requirements,a user labels some DOM elements on the page with attribute names.The common features of the labeled elements are utilized to guide the user through the labeling process to minimize user efforts,and are also utilized to retrieve attribute values.To turn the attribute values into a structured result,the attribute pattern needs to be induced.For this purpose,a space-optimized suffix tree called attribute tree is built to transform the document object model(DOM) tree into a simpler form while preserving its useful properties such as attribute sequence order.The pattern is induced bottom-up on the attribute tree,and is further used to build the structured result.Experiments are conducted and show high performance of our approach in terms of precision,recall and structural correctness.
