This paper presents ASC03 algorithm, aimed at finding mappings between entities of two ontologies represented in OWL DL/Lite. ASC03 algorithm searches the maximal common subgraph of two graphs representing two ontologies, and relies on an algorithm of search of the maximal clique of their association graph.
{"title":"A Graph-Based Algorithm for Alignment of OWL Ontologies","authors":"B. Le, R. Dieng","doi":"10.1109/WI.2007.10","DOIUrl":"https://doi.org/10.1109/WI.2007.10","url":null,"abstract":"This paper presents ASC03 algorithm, aimed at finding mappings between entities of two ontologies represented in OWL DL/Lite. ASC03 algorithm searches the maximal common subgraph of two graphs representing two ontologies, and relies on an algorithm of search of the maximal clique of their association graph.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114925352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Computer science is entering a new generation. The previous generation was based on abstracting from hardware. The emerging generation comes from abstracting from software and sees all resources as services in a service-oriented architecture (SOA). In a world of services, it is the service that counts for a customer and not the software or hardware components that implement the service. Service-oriented architectures are rapidly becoming the dominant computing paradigm. However, current SOA solutions are still restricted in their application context to in-house solution of companies. A service web will have billions of services. While service orientation is widely acknowledged for its potential to revolutionize the world of computing by abstracting form underlying hardware and software layers, that success depends on resolving fundamental challenges that SOA does not address currently. The mission of Service Web 3.0 is to provide solutions to integration and search that will enable the Service Oriented Architecture (SOA) revolution on a worldwide scale. Hereby we must focus on three major areas where we need to extend current approaches towards service orientation:
计算机科学正在进入新时代。上一代基于对硬件的抽象。新兴一代来自于对软件的抽象，并将所有资源视为面向服务的体系结构(SOA)中的服务。在服务的世界中，对客户来说重要的是服务，而不是实现服务的软件或硬件组件。面向服务的体系结构正迅速成为占主导地位的计算范式。然而，当前的SOA解决方案在其应用程序上下文中仍然局限于公司的内部解决方案。一个服务网将拥有数十亿个服务。虽然面向服务被广泛认为具有从底层硬件和软件层进行抽象来彻底改变计算世界的潜力，但这种成功取决于解决SOA目前没有解决的基本挑战。Service Web 3.0的使命是为集成和搜索提供解决方案，从而在全球范围内实现面向服务的体系结构(Service Oriented Architecture, SOA)革命。因此，我们必须把重点放在三个主要领域，在这些领域我们需要扩展当前面向服务的方法:
{"title":"ServiceWeb 3.0","authors":"D. Fensel","doi":"10.1109/IAT.2007.92","DOIUrl":"https://doi.org/10.1109/IAT.2007.92","url":null,"abstract":"Computer science is entering a new generation. The previous generation was based on abstracting from hardware. The emerging generation comes from abstracting from software and sees all resources as services in a service-oriented architecture (SOA). In a world of services, it is the service that counts for a customer and not the software or hardware components that implement the service. Service-oriented architectures are rapidly becoming the dominant computing paradigm. However, current SOA solutions are still restricted in their application context to in-house solution of companies. A service web will have billions of services. While service orientation is widely acknowledged for its potential to revolutionize the world of computing by abstracting form underlying hardware and software layers, that success depends on resolving fundamental challenges that SOA does not address currently. The mission of Service Web 3.0 is to provide solutions to integration and search that will enable the Service Oriented Architecture (SOA) revolution on a worldwide scale. Hereby we must focus on three major areas where we need to extend current approaches towards service orientation:","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122810176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Finding and keeping track of other researchers' publication lists is an essential activity for every researcher, because they often contain citations not found elsewhere and may provide access to information, such as slides and talks, which can help other researchers keep abreast of state-of- the-art knowledge and technology. There are many different ways to generate publication list web pages, and a researcher may have several different versions of a publication list on the Web because he holds different positions. So it is difficult to find the correct publication list web page from the top results retrieved from search engines, especially when we only know the name of the researcher. Very few works have addressed the problem. In this paper, we propose a system called the "publication list Web page finder" (PLF), which can automatically find the publication list Web pages for a given researcher's name. The PLF system is an automatic and language-independent system, and its main idea is that publication list Web pages often contain many citations about a specific researcher, so the system uses those citations as clues to find out publication list web pages. Our experimental results show that the PLF system outperforms other approaches, especially when a researcher has multiple publication list Web pages.
{"title":"PLF: A Publication List Web Page Finder for Researchers","authors":"Kai-Hsiang Yang, Jen-Ming Chung, Jan-Ming Ho","doi":"10.1109/WI.2007.85","DOIUrl":"https://doi.org/10.1109/WI.2007.85","url":null,"abstract":"Finding and keeping track of other researchers' publication lists is an essential activity for every researcher, because they often contain citations not found elsewhere and may provide access to information, such as slides and talks, which can help other researchers keep abreast of state-of- the-art knowledge and technology. There are many different ways to generate publication list web pages, and a researcher may have several different versions of a publication list on the Web because he holds different positions. So it is difficult to find the correct publication list web page from the top results retrieved from search engines, especially when we only know the name of the researcher. Very few works have addressed the problem. In this paper, we propose a system called the \"publication list Web page finder\" (PLF), which can automatically find the publication list Web pages for a given researcher's name. The PLF system is an automatic and language-independent system, and its main idea is that publication list Web pages often contain many citations about a specific researcher, so the system uses those citations as clues to find out publication list web pages. Our experimental results show that the PLF system outperforms other approaches, especially when a researcher has multiple publication list Web pages.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127908247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Sasajima, Y. Kitamura, Takefumi Naganuma, S. Kurakake, R. Mizoguchi
Growth in the mobile services industry has remarkably increased in the number of mobile services provided, and present methods of service provision have proven insufficient to guide users efficiently to the services they need. To solve this problem, a task-oriented menu, which enables users to search for services by "what they want to do" instead of by "name of category", has been proposed. Construction of such a task-oriented menu is based on a task ontology modeling method which supports the description of user activity such as task execution and the solving of obstacles encountered during the task. This paper discusses a task ontology-based modeling method which supports the description of users' activity and related knowledge such as how to solve problems that occurs on the users and prevention method for accidents. Models described by our method contribute to checking, designing and improving mobile Internet services.
{"title":"OOPS: User Modeling Method for Task Oriented Mobile Internet Services","authors":"M. Sasajima, Y. Kitamura, Takefumi Naganuma, S. Kurakake, R. Mizoguchi","doi":"10.1109/WI.2007.143","DOIUrl":"https://doi.org/10.1109/WI.2007.143","url":null,"abstract":"Growth in the mobile services industry has remarkably increased in the number of mobile services provided, and present methods of service provision have proven insufficient to guide users efficiently to the services they need. To solve this problem, a task-oriented menu, which enables users to search for services by \"what they want to do\" instead of by \"name of category\", has been proposed. Construction of such a task-oriented menu is based on a task ontology modeling method which supports the description of user activity such as task execution and the solving of obstacles encountered during the task. This paper discusses a task ontology-based modeling method which supports the description of users' activity and related knowledge such as how to solve problems that occurs on the users and prevention method for accidents. Models described by our method contribute to checking, designing and improving mobile Internet services.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128228245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we present a method for tagging web pages using more formal conceptual structures than a set of keywords. We have developed a formal Tag model and a method to map a set of keywords on it. Moreover, this model is used as the basis for the conceptual tag refinement, which searches for terms which are conceptually related to the tags that are assigned to an information source. In that way the meaning of the tags can be disambiguated, which supports a better usage of tags for further management of tagged documents. We have developed a software tool, an annotation framework, which realizes this approach. We present results from the first evaluation studies regarding its application for ontology pruning.
{"title":"On the Conceptual Tagging: An Ontology Pruning Use Case","authors":"Ljiljana Stojanović, N. Stojanović, Jun Ma","doi":"10.1109/WI.2007.81","DOIUrl":"https://doi.org/10.1109/WI.2007.81","url":null,"abstract":"In this paper we present a method for tagging web pages using more formal conceptual structures than a set of keywords. We have developed a formal Tag model and a method to map a set of keywords on it. Moreover, this model is used as the basis for the conceptual tag refinement, which searches for terms which are conceptually related to the tags that are assigned to an information source. In that way the meaning of the tags can be disambiguated, which supports a better usage of tags for further management of tagged documents. We have developed a software tool, an annotation framework, which realizes this approach. We present results from the first evaluation studies regarding its application for ontology pruning.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114016701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Wetzker, T. Alpcan, C. Bauckhage, Winfried Umbrath, S. Albayrak
We propose a hierarchical approach to document categorization that requires no pre-configuration and maps the semantic document space to a predefined taxonomy. The utilization of search engines to train a hierarchical classifier makes our approach more flexible than existing solutions which rely on (human) labeled data and are bound to a specific domain. We show that the structural information given by the taxonomy allows for a context aware construction of search queries and leads to higher tagging accuracy. We test our approach on different benchmark datasets and evaluate its performance on the single- and multi-tag assignment tasks. The experimental results show that our solution is as accurate as supervised classifiers for web page classification and still performs well when categorizing domain specific documents.
{"title":"An unsupervised hierarchical approach to document categorization","authors":"R. Wetzker, T. Alpcan, C. Bauckhage, Winfried Umbrath, S. Albayrak","doi":"10.1109/WI.2007.21","DOIUrl":"https://doi.org/10.1109/WI.2007.21","url":null,"abstract":"We propose a hierarchical approach to document categorization that requires no pre-configuration and maps the semantic document space to a predefined taxonomy. The utilization of search engines to train a hierarchical classifier makes our approach more flexible than existing solutions which rely on (human) labeled data and are bound to a specific domain. We show that the structural information given by the taxonomy allows for a context aware construction of search queries and leads to higher tagging accuracy. We test our approach on different benchmark datasets and evaluate its performance on the single- and multi-tag assignment tasks. The experimental results show that our solution is as accurate as supervised classifiers for web page classification and still performs well when categorizing domain specific documents.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114367176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate the problem of identifying both product properties and opinion words for sentences in a unified process when only a much small labeled corpus is available. Naive Bayesian method is used in this process. Specifically, considering the fact that product properties and opinion words usually co-occur with high frequency in product review articles, a cross- training method is proposed to bootstrap both of them, in which the two sub-tasks are boosted by each other iteratively. Experiment results show that with a much small labeled corpus cross-training could produce both product properties and opinion words which are very close to what Naive Bayesian Classifiers could do with a large labeled corpus..
{"title":"Bootstrapping both Product Properties and Opinion Words from Chinese Reviews with Cross-Training","authors":"Bo Wang, Houfeng Wang","doi":"10.1109/WI.2007.32","DOIUrl":"https://doi.org/10.1109/WI.2007.32","url":null,"abstract":"We investigate the problem of identifying both product properties and opinion words for sentences in a unified process when only a much small labeled corpus is available. Naive Bayesian method is used in this process. Specifically, considering the fact that product properties and opinion words usually co-occur with high frequency in product review articles, a cross- training method is proposed to bootstrap both of them, in which the two sub-tasks are boosted by each other iteratively. Experiment results show that with a much small labeled corpus cross-training could produce both product properties and opinion words which are very close to what Naive Bayesian Classifiers could do with a large labeled corpus..","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133283772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hongbing Wang, Hui Liu, Chen Wang, Patrick C. K. Hung
This paper is based on the theory of Finite State Automata (FSA's), models a web service as a FSA, extends WSDL for conceptually describing the behaviors of Web services, and introduces the concept of Temporal Logic of Actions (short for TLA) to describe and specify the behavior of a service in a formal way.
{"title":"A New Approach to Describe Web Services","authors":"Hongbing Wang, Hui Liu, Chen Wang, Patrick C. K. Hung","doi":"10.1109/WI.2007.12","DOIUrl":"https://doi.org/10.1109/WI.2007.12","url":null,"abstract":"This paper is based on the theory of Finite State Automata (FSA's), models a web service as a FSA, extends WSDL for conceptually describing the behaviors of Web services, and introduces the concept of Temporal Logic of Actions (short for TLA) to describe and specify the behavior of a service in a formal way.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134361067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the Web becomes the major information source of our daily activities, tools for finding various information on it are indispensable. This paper addresses theWeb retrieval of instance-attribute information, e.g., the contact addresses and research interests (attributes) of faculty and students (instances). This kind of information need is very common but cannot be directly supported by current keywordmatching-based search engines. People commonly use a two-phase search: First, locate the candidate pages, e.g., a faculty page, and then search within them for the desired information, e.g., contact information. Based on the stimulation of such human search behavior, we design a retrieval engine, upon general search engines, to help find the instance-attribute information from the Web. The experiment on several faculty members has shown the feasibility of the approach.
{"title":"Instant Web Retrieval for Instance-Attribute Queries","authors":"Yi-Ting Chou, Shui-Lung Chuang, Xuanhui Wang","doi":"10.1109/WI.2007.67","DOIUrl":"https://doi.org/10.1109/WI.2007.67","url":null,"abstract":"As the Web becomes the major information source of our daily activities, tools for finding various information on it are indispensable. This paper addresses theWeb retrieval of instance-attribute information, e.g., the contact addresses and research interests (attributes) of faculty and students (instances). This kind of information need is very common but cannot be directly supported by current keywordmatching-based search engines. People commonly use a two-phase search: First, locate the candidate pages, e.g., a faculty page, and then search within them for the desired information, e.g., contact information. Based on the stimulation of such human search behavior, we design a retrieval engine, upon general search engines, to help find the instance-attribute information from the Web. The experiment on several faculty members has shown the feasibility of the approach.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131278324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose two novel web-based metrics for semantic similarity computation between words. Both metrics use a web search engine in order to exploit the retrieved information for the words of interest. The first metric considers only the page counts returned by a search engine, based on the work of [1]. The second downloads a number of the top ranked documents and applies "widecontext" and "narrow-context" metrics. The proposed metrics work automatically, without consulting any human annotated knowledge resource. The metrics are compared with WordNet-based methods. The metrics' performance is evaluated in terms of correlation with respect to the pairs of the commonly used Charles - Miller dataset. The proposed "wide-context" metric achieves 71% correlation, which is the highest score achieved among the fully unsupervised metrics in the literature up to date.
{"title":"Unsupervised Semantic Similarity Computation using Web Search Engines","authors":"Elias Iosif, A. Potamianos","doi":"10.1109/WI.2007.104","DOIUrl":"https://doi.org/10.1109/WI.2007.104","url":null,"abstract":"In this paper, we propose two novel web-based metrics for semantic similarity computation between words. Both metrics use a web search engine in order to exploit the retrieved information for the words of interest. The first metric considers only the page counts returned by a search engine, based on the work of [1]. The second downloads a number of the top ranked documents and applies \"widecontext\" and \"narrow-context\" metrics. The proposed metrics work automatically, without consulting any human annotated knowledge resource. The metrics are compared with WordNet-based methods. The metrics' performance is evaluated in terms of correlation with respect to the pairs of the commonly used Charles - Miller dataset. The proposed \"wide-context\" metric achieves 71% correlation, which is the highest score achieved among the fully unsupervised metrics in the literature up to date.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122694654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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