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IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)最新文献

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RDF(S) and SPARQL Expressiveness in Engineering Design Patterns 工程设计模式中的RDF(S)和SPARQL表达性
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.89
Hacène Cherfi, O. Corby, Cyril Masia Tissot
{"title":"RDF(S) and SPARQL Expressiveness in Engineering Design Patterns","authors":"Hacène Cherfi, O. Corby, Cyril Masia Tissot","doi":"10.1109/WI.2007.89","DOIUrl":"https://doi.org/10.1109/WI.2007.89","url":null,"abstract":"In engineering product design, using RDF(s) semantic Web (SW) language, the number of instances to handle is usually large. We want to easily put additional information on property values and metadata over selected instances. Moreover, we want to use standard SPARQL in order to query the RDF graph. We have designed solutions to address a family of problems related to instance property values in engineering design patterns (order, metadata, etc.).","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":"127807969","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}
引用次数: 2
A Goal Specification Language for Automated Discovery and Composition of Web Services 用于自动发现和组合Web服务的目标规范语言
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.9
{"title":"A Goal Specification Language for Automated Discovery and Composition of Web Services","authors":"","doi":"10.1109/WI.2007.9","DOIUrl":"https://doi.org/10.1109/WI.2007.9","url":null,"abstract":"In order to find suitableWeb services from a large collection of Web services, automatic support is needed to filter out Web services relevant according to some criteria specified by the user. In real business scenarios constraints on the types of input and output parameters are often not sufficient. Rather one wishes to specify constraints on relationships of input and output parameters, interaction pattern and non-functional properties ofWeb services. Therefore, there is a need for a more expressive goal specification language. Current goal specification techniques for matchmaking and composition of Web services either lack expressivity to support real business scenarios or formal semantics to enable development of automatic algorithms. In this paper, we present a goal specification language that allow specifying constraints on functional and nonfunctional properties of Web services. The language is a novel combination of an expressive temporal logic ì- calculus and an expressive description logic SHIQ(D).","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"143 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":"116402527","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}
引用次数: 18
Baum-Welch Style EM Approach on Simple Bayesian Models forWeb Data Annotation 基于简单贝叶斯模型的web数据标注Baum-Welch风格EM方法
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.124
S. Masum, H. Prendinger, M. Ishizuka
{"title":"Baum-Welch Style EM Approach on Simple Bayesian Models forWeb Data Annotation","authors":"S. Masum, H. Prendinger, M. Ishizuka","doi":"10.1109/WI.2007.124","DOIUrl":"https://doi.org/10.1109/WI.2007.124","url":null,"abstract":"In this paper, our focus will be on weakly annotated data (WAD) which is typically generated by a (semi) automated information extraction system from the Web documents. The extracted information has a certain level of accuracy which can be surpassed by using statistical models that are capable of contextual reasoning such as Bayesian models. Our contribution is an EM algorithm that operates on simple Bayesian models to re-annotate WAD. EM estimates the parameters, i.e., the prior and conditional probabilities by iterating Bayesian model on the given Web data. In the expectation step, Bayesian classifier is trained from current annotations, and in the maximization step, the roles of all the labels are re-annotated to find the best fitting annotation with the current model then the probabilities are re-adjusted from the new annotations. Our experiments show that EM increases the Web data annotation accuracies up to 8%. We use Baum-Welch methodology in our EM approach.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"7 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":"121802423","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}
引用次数: 1
Web Personalisation Through Incremental Individual Profiling and Support-based User Segmentation 通过增量个人分析和基于支持的用户细分实现Web个性化
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.111
Yiyu Yao, Yi Zeng, N. Zhong, Xiangji Huang
{"title":"Web Personalisation Through Incremental Individual Profiling and Support-based User Segmentation","authors":"Yiyu Yao, Yi Zeng, N. Zhong, Xiangji Huang","doi":"10.1109/WI.2007.111","DOIUrl":"https://doi.org/10.1109/WI.2007.111","url":null,"abstract":"Online personalised \"my*\" services are gaining popularity due to a growing customer need for information filtering and customisation. However, current systems mostly rely on some general usage and customer interaction in selecting components from prespecified blocks of content. The demand is great for high-quality unsupervised services on the customer side and for enabling techniques on the vendor side. Furthermore, individual profiles and, thus, personalised content should reflect changing individual behaviour. How do we efficiently build and maintain up-to-date personalised services for a large number of individuals? A compact and efficient, incrementally updatable representation of individual profiles is crucial. In addition, methods are required for efficient comparison of such profiles. Here we propose a methodology for building up-to-date personalised services. Individual profiles are represented as space-efficient prefix trees that are inherently easy to update incrementally. To measure the similarity of profiles, and also for the purpose of segmentation, we define a support-based metric that exploits the advantages of the tree-based structure. We evaluate our method on anonymised web data of 10,000 customers of an investment bank collected over 1.5 years.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"14 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":"126440355","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}
引用次数: 45
Experimental Bounds on the Usefulness of Personalized and Topic-Sensitive PageRank 个性化和主题敏感PageRank有用性的实验边界
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.130
Sinan Al-Saffar, G. Heileman
{"title":"Experimental Bounds on the Usefulness of Personalized and Topic-Sensitive PageRank","authors":"Sinan Al-Saffar, G. Heileman","doi":"10.1109/WI.2007.130","DOIUrl":"https://doi.org/10.1109/WI.2007.130","url":null,"abstract":"PageRank is an algorithm used by several search engines to rank web documents according to their assumed relevance and popularity deduced from the Web's link structure. PageRank determines a global ordering of candidate search results according to each page's popularity as determined by the number and importance of pages linking to these results. Personalized and topic-sensitive PageRank are variants of the algorithm that return a local ranking based on each user's preferences as biased by a set of pages they trust or topics they prefer. In this paper we compare personalized and topic-sensitive local PageRanks to the global PageRank showing experimentally how similar or dissimilar results of personalization can be to the original global rank results and to other personalizations. Our approach is to examine a snapshot of the Web and determine how advantageous personalization can be in the best and worst cases and how it performs at various values of the damping factor in the PageRank formula.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"61 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":"132189349","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}
引用次数: 26
An Integrative Semantic Framework for Image Annotation and Retrieval 图像标注与检索的集成语义框架
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.17
T. Osman, D. Thakker, Gerald Schaefer, Phil Lakin
{"title":"An Integrative Semantic Framework for Image Annotation and Retrieval","authors":"T. Osman, D. Thakker, Gerald Schaefer, Phil Lakin","doi":"10.1109/WI.2007.17","DOIUrl":"https://doi.org/10.1109/WI.2007.17","url":null,"abstract":"Most public image retrieval engines utilise free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. Our semantic retrieval technology is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. We also present our efforts in further improving the recall of our retrieval technology by deploying an efficient query expansion technique.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"2 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":"132494133","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}
引用次数: 27
Leveraging Webpage Classification for Data Object Recognition 利用网页分类进行数据对象识别
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.140
Ling Lin, Lizhu Zhou
{"title":"Leveraging Webpage Classification for Data Object Recognition","authors":"Ling Lin, Lizhu Zhou","doi":"10.1109/WI.2007.140","DOIUrl":"https://doi.org/10.1109/WI.2007.140","url":null,"abstract":"Data-rich webpages are providing an increasingly important data source for web applications. While the problem of data object recognition is intensively discussed, it is mostly addressed as a separated process from the frontier task of relevant webpage identification. In this paper, we propose a method to leverage the classification result of data-rich webpages for efficient and scalable data object recognition. A novel context information is proposed, which can be inferred from the webpage classification and exploited in the bottom-up data object recognition. Experimental results show that the context information brings a 19% improvement in the running efficiency of the bottom- up data object recognition.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"1 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":"130500755","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}
引用次数: 8
Measuring Semantic Similarity between Named Entities by Searching the Web Directory 通过搜索Web目录测量命名实体之间的语义相似度
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.75
Jiahui Liu, L. Birnbaum
{"title":"Measuring Semantic Similarity between Named Entities by Searching the Web Directory","authors":"Jiahui Liu, L. Birnbaum","doi":"10.1109/WI.2007.75","DOIUrl":"https://doi.org/10.1109/WI.2007.75","url":null,"abstract":"The importance of named entities in information retrieval and knowledge management has recently brought interest in characterizing semantic relationships between entities. In this paper, we propose a method for measuring semantic similarity, an important type of semantic relationship, between entities. The method is based on Google Directory, a search interface to the Open Directory Project. Via the search engine, we can locate the web pages relevant to an entity and automatically create a profile of the entity according to the directory assignments of its web pages, which capture various features of the entity. Using their profiles, the semantic similarity between entities can be measured in different dimensions. We apply the semantic similarity measurement to two knowledge acquisition tasks: thesaurus construction of entities and fine grained categorization of entities. Our experiments demonstrate that the proposed method works effectively in these two tasks.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"172 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":"116630517","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}
引用次数: 41
Mining Context-based User Preferences for m-Services Applications 为移动服务应用挖掘基于上下文的用户偏好
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.141
E. Jembere, M. Adigun, S. S. Xulu
{"title":"Mining Context-based User Preferences for m-Services Applications","authors":"E. Jembere, M. Adigun, S. S. Xulu","doi":"10.1109/WI.2007.141","DOIUrl":"https://doi.org/10.1109/WI.2007.141","url":null,"abstract":"Human Computer Interaction (HCI) challenges in mobile computing can be addressed by tailoring access and use of mobile services to user preferences. Our investigation of existent approaches to personalisation in context-aware computing found that user preferences are assumed to be static across different context descriptions, whilst in reality some user preferences are transient and vary with the change in context. Furthermore, existent preference models do not give an intuitive interpretation of a preference and lack user expressiveness. To tackle these issues, this paper presents a user preference model and mining framework for a context-aware m-services environment based on an intuitive quantitative preference measure and a strict partial order preference representation. Experimental evaluation of the user preference mining framework in a simulated m-Commerce environment showed that it is very promising. The preference mining algorithms were found to scale well with increases in the volumes of data.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"43 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":"129149006","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}
引用次数: 18
COBRA - Mining Web for Corporate Brand and Reputation Analysis COBRA -企业品牌和声誉分析的挖掘网络
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.3233/WIA-2009-0166
W. Spangler, Ying Chen, Larry Proctor, A. Lelescu, Amit Behal, Bin He, Thomas D. Griffin, Anna Liu, B. Wade, Trevor Davis
{"title":"COBRA - Mining Web for Corporate Brand and Reputation Analysis","authors":"W. Spangler, Ying Chen, Larry Proctor, A. Lelescu, Amit Behal, Bin He, Thomas D. Griffin, Anna Liu, B. Wade, Trevor Davis","doi":"10.3233/WIA-2009-0166","DOIUrl":"https://doi.org/10.3233/WIA-2009-0166","url":null,"abstract":"Corporations are extremely sensitive to issues such as brand stewardship and product reputation. Traditional brand image and reputation tracking is limited to news wires and contact centres analysis. However, with the emergence of Web, consumer generated media (COM), such as blogs, news forums, message boards, and Web pages/sites, is rapidly becoming the \"voice of the people\". This paper describes a COBRA (corporate brand and reputation analysis) solution that mines a wide range of COM contents for brand and reputation analysis. The solution contains a flexible ETL (Extract, Transform, and Load) engine that processes diverse sets of structured and unstructured information, a suite of analytical capabilities that mines COM content to extract semantic entities and insights out of the data, and an alerting mechanism that utilizes the analytics results to accurately generate brand and reputation alerts. We use a real-world case study to demonstrate the effectiveness of our approach.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"15 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":"125531989","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}
引用次数: 48
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