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

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Recurrent Neural Networks for Robust Real-World Text Classification 用于鲁棒现实世界文本分类的递归神经网络
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.91
Ali Mohammad Zareh Bidoki, Nasser Yazdani, Pedram Ghodsnia
{"title":"Recurrent Neural Networks for Robust Real-World Text Classification","authors":"Ali Mohammad Zareh Bidoki, Nasser Yazdani, Pedram Ghodsnia","doi":"10.1109/WI.2007.91","DOIUrl":"https://doi.org/10.1109/WI.2007.91","url":null,"abstract":"This paper explores the application of recurrent neural networks for the task of robust text classification of a real-world benchmarking corpus. There are many well-established approaches which are used for text classification, but they fail to address the challenge from a more multi-disciplinary viewpoint such as natural language processing and artificial intelligence. The results demonstrate that these recurrent neural networks can be a viable addition to the many techniques used in web intelligence for tasks such as context sensitive email classification and web site indexing.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"248 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":"124732210","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: 25
Automatic Website Comprehensibility Evaluation 自动网站可理解性评估
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.27
Ping Yan, Zhu Zhang, Ray Garcia
{"title":"Automatic Website Comprehensibility Evaluation","authors":"Ping Yan, Zhu Zhang, Ray Garcia","doi":"10.1109/WI.2007.27","DOIUrl":"https://doi.org/10.1109/WI.2007.27","url":null,"abstract":"The Web provides easy access to a vast amount of informational content to the average person, who may often be interested in selecting Websites that best match their learning objectives and comprehensibility level. Web content is generally not tagged for easy determination of its instructional appropriateness and comprehensibility level. Our research develops an analytical model, using a group of website features, to automatically determine the comprehensibility level of a Website. These features, selected from a large pool of Website features quantitatively measured, are statistically shown to be significantly correlated to website comprehensibility based on empirical studies. The automatically inferred comprehensibility index may be used to assist the average person, interested in using web content for self-directed learning, to find content suited to their comprehension level and filter out content which may have low potential instructional value.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"51 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":"115102538","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: 15
Geographically-Sensitive Link Analysis 地理敏感链接分析
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.134
Hyun Chul Lee, Haifeng Liu, Renée J. Miller
{"title":"Geographically-Sensitive Link Analysis","authors":"Hyun Chul Lee, Haifeng Liu, Renée J. Miller","doi":"10.1109/WI.2007.134","DOIUrl":"https://doi.org/10.1109/WI.2007.134","url":null,"abstract":"Many web pages and resources are primarily relevant to certain geographic locations. For example, in many queries web pages on restaurants, hotels, or movie theaters are mostly relevant to those users who are in geographic proximity to these locations. Moreover, as the number of queries with a local component increases, searching for web pages which are relevant to geographic locations is becoming increasingly important. The performance of geographically-oriented search is greatly affected by how we use geographic information to rank web pages. In this paper, we study the issue of ranking web pages using geographically-sensitive link analysis algorithms. More precisely, we study the question of whether geographic information can improve search performance. We propose several geographically-sensitive link analysis algorithms which exploit the geographic linkage between pages. We empirically analyze the performance of our algorithms.","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":"116085251","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: 10
FICA: A Fast Intelligent Crawling Algorithm 一种快速智能爬行算法
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.132
Shady Shehata, F. Karray, Mohamed S. Kamel
{"title":"FICA: A Fast Intelligent Crawling Algorithm","authors":"Shady Shehata, F. Karray, Mohamed S. Kamel","doi":"10.1109/WI.2007.132","DOIUrl":"https://doi.org/10.1109/WI.2007.132","url":null,"abstract":"Due to the proliferation and highly dynamic nature of the Web, an efficient crawling and ranking algorithm for retrieving the most important pages has remained as a challenging issue. Several algorithms like PageRank (Page et al., 1998) and OPIC (Abiteboul et al., 2003) have been proposed. Unfortunately, they have high time complexity. In this paper, an intelligent crawling algorithm based on reinforcement learning, called FICA is proposed that models a real surfing user. The priority for crawling pages is based on a concept which we name as logarithmic distance. FICA is easy to implement and its time complexity is 0(E*logV) where V and E are the number of nodes and edges in the Web graph respectively. Comparison of the FICA with other proposed algorithms shows that FICA outperforms them in discovering highly important pages. Furthermore FICA computes the importance (ranking) of each page during the crawling process. Thus, we can also use FICA as a ranking method for computation of page importance. We have used UK's Web graph for our experiments.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"51 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":"117280906","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: 21
Finding Event-Relevant Content from the Web Using a Near-Duplicate Detection Approach 使用近重复检测方法从Web中查找事件相关内容
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.58
Hung-Chi Chang, Jenq-Haur Wang, Chih-Yi Chiu
{"title":"Finding Event-Relevant Content from the Web Using a Near-Duplicate Detection Approach","authors":"Hung-Chi Chang, Jenq-Haur Wang, Chih-Yi Chiu","doi":"10.1109/WI.2007.58","DOIUrl":"https://doi.org/10.1109/WI.2007.58","url":null,"abstract":"In online resources, such as news and weblogs, authors often extract articles, embed content, and comment on existing articles related to a popular event. Therefore, it is useful if authors can check whether two or more articles share common parts for further analysis, such as cocitation analysis and search result improvement. If articles do have parts in common, we say the content of such articles is event-relevant. Conventional text classification methods classify a complete document into categories, but they cannot represent the semantics precisely or extract meaningful event-relevant content. To resolve these problems, we propose a near-duplicate detection approach for finding event-relevant content in Web documents. The efficiency of the approach and the proposed duplicate set generation algorithms make it suitable for identifying event-relevant content. The experiment results demonstrate the potential of the proposed approach for use in weblogs.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"77 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":"123505762","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
Ontology Mining for Personalized Web Information Gathering 面向个性化Web信息采集的本体挖掘
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.82
Xiaohui Tao, Yuefeng Li, N. Zhong, R. Nayak
{"title":"Ontology Mining for Personalized Web Information Gathering","authors":"Xiaohui Tao, Yuefeng Li, N. Zhong, R. Nayak","doi":"10.1109/WI.2007.82","DOIUrl":"https://doi.org/10.1109/WI.2007.82","url":null,"abstract":"It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of \"kind-of\", \"part-of\", and \"related-to\" and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"25 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":"114763704","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: 140
Mapping Ontologies Elements using Features in a Latent Space 使用潜在空间中的特征映射本体元素
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.74
Vassilis Spiliopoulos, G. Vouros, V. Karkaletsis
{"title":"Mapping Ontologies Elements using Features in a Latent Space","authors":"Vassilis Spiliopoulos, G. Vouros, V. Karkaletsis","doi":"10.1109/WI.2007.74","DOIUrl":"https://doi.org/10.1109/WI.2007.74","url":null,"abstract":"This paper proposes a method for the mapping of ontologies that, in a greater extent than other approaches, discovers and exploits sets of latent features for approximating the intended meaning of ontology elements. This is done by applying the reverse generative process of the Latent Dirichlet Allocation model. Similarity between element pairs is computed by means of the Kullback-Leibler divergence measure. Experimental results show the potential of the method.","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":"128165944","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
Content Extraction from News Pages Using Particle Swarm Optimization on Linguistic and Structural Features 基于语言和结构特征的粒子群优化新闻页面内容提取
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.38
Cai-Nicolas Ziegler, Michal Skubacz
{"title":"Content Extraction from News Pages Using Particle Swarm Optimization on Linguistic and Structural Features","authors":"Cai-Nicolas Ziegler, Michal Skubacz","doi":"10.1109/WI.2007.38","DOIUrl":"https://doi.org/10.1109/WI.2007.38","url":null,"abstract":"Today's Web pages are commonly made up of more than merely one cohesive block of information. For instance, news pages from popular media channels such as Financial Times or Washington Post consist of no more than 30%-50% of textual news, next to advertisements, link lists to related articles, disclaimer information, and so forth. However, for many search-oriented applications such as the detection of relevant pages for an in-focus topic, dissecting the actual textual content from surrounding page clutter is an essential task, so as to maintain appropriate levels of document retrieval accuracy. We present a novel approach that extracts real content from news Web pages in an unsupervised fashion. Our method is based on distilling linguistic and structural features from text blocks in HTML pages, having a particle swarm optimizer (PSO) learn feature thresholds for optimal classification performance. Empirical evaluations and benchmarks show that our approach works very well when applied to several hundreds of news pages from popular media in 5 languages.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"20 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":"132805794","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: 43
Supporting Web Searching of Business Intelligence with Information Visualization 利用信息可视化支持商业智能的Web搜索
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.149
Wingyan Chung, Ada Leung
{"title":"Supporting Web Searching of Business Intelligence with Information Visualization","authors":"Wingyan Chung, Ada Leung","doi":"10.1109/WI.2007.149","DOIUrl":"https://doi.org/10.1109/WI.2007.149","url":null,"abstract":"In this research, we proposed and validated an approach to using information visualization to augment search engines in supporting the analysis of business stakeholder information on the Web. We report in this paper findings from a preliminary evaluation comparing a visualization prototype with a traditional method of stakeholder analysis (Web browsing and searching). We found that the prototype achieved a higher perceived usefulness and perceived analysis effectiveness and was perceived favorably in expediting the subjects' decision making and in helping them understand the analysis results. Overall, the proposed approach was found to augment traditional methods of analyzing business stakeholders. We discuss implications to researchers and practitioners and future directions.","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":"126595690","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: 6
Layers and Hierarchies in Real Virtual Networks 真实虚拟网络中的层次结构
IEEE/WIC/ACM International Conference on Web Intelligence (WI'07) Pub Date : 2007-11-02 DOI: 10.1109/WI.2007.69
Olga Goussevskaia, Michael Kuhn, Roger Wattenhofer
{"title":"Layers and Hierarchies in Real Virtual Networks","authors":"Olga Goussevskaia, Michael Kuhn, Roger Wattenhofer","doi":"10.1109/WI.2007.69","DOIUrl":"https://doi.org/10.1109/WI.2007.69","url":null,"abstract":"The virtual world is comprised of data items related to each other in a variety of contexts. Often such relations can be represented as graphs that evolve over time. Examples include social networks, co-authorship graphs, and the world-wide-web. Attempts to model these graphs have introduced the notions of hierarchies and layers, which correspond to taxonomies of the underlying objects, and reasons for object relations, respectively. In this paper we explore these concepts in the process of mining such naturallygrown networks. Based on two sample graphs, we present some evidence that the current models well fit real world networks and provide concrete applications of these findings. In particular, we show how hierarchies can be used for greedy routing and how separation of layers can be used as a preprocessing step to implement a location estimation application.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"92 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":"115579279","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
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