2011 IEEE Fifth International Conference on Semantic Computing最新文献

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Retrieval of Patent Documents from Heterogeneous Sources Using Ontologies and Similarity Analysis 基于本体和相似度分析的异构专利文献检索
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.34
Siddharth Taduri, Gloria T. Lau, K. Law, J. Kesan
{"title":"Retrieval of Patent Documents from Heterogeneous Sources Using Ontologies and Similarity Analysis","authors":"Siddharth Taduri, Gloria T. Lau, K. Law, J. Kesan","doi":"10.1109/ICSC.2011.34","DOIUrl":"https://doi.org/10.1109/ICSC.2011.34","url":null,"abstract":"In the past few years, there has been an explosive growth in scientific and legal information related to the patent system. Patents and related documents are siloed into multiple heterogeneous sources. Retrieving relevant information from diverse sources is a non-trivial task and poses many technical challenges. Among the challenges is the issue of terminological inconsistencies that are used in the documents. We tackle the terminological inconsistency issue by exploring domain knowledge through the use of ontology standards. Furthermore, we take advantage of cross-references and structural dependencies between the information sources to enhance terminological comparison. In this paper, we present a similarity analysis methodology which combines knowledge from two distinct sources -- (1) domain ontologies and (2) ontologies which describe the information sources to assist a user in identifying relevant documents across several information sources simultaneously. Specifically, we explore the use of a rule-based system to infer relationships between documents based on pre-defined heuristics. We present our results through a use case in the bio-patent domain with a collection of 1150 patents and 30 court cases.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"42 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122830192","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: 9
Characterization and Analysis of Emergent Image Semantics Using Network Models 基于网络模型的突发图像语义表征与分析
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.58
Rahul Singh, Ryohei Nakata, Joseph Downs
{"title":"Characterization and Analysis of Emergent Image Semantics Using Network Models","authors":"Rahul Singh, Ryohei Nakata, Joseph Downs","doi":"10.1109/ICSC.2011.58","DOIUrl":"https://doi.org/10.1109/ICSC.2011.58","url":null,"abstract":"Understanding and dealing with the emergent semantics of image and media-based information is one of the most challenging aspects of theoretical, algorithmic, and systems-oriented research in Multimedia. Emergent semantics implies that media is endowed with meaning by placing it in context of other similar media and through factors that are user specific. This means that unlike alphanumeric data, a fixed semantics cannot be assigned to media. While this intriguing property of media-based information has been known for nearly a decade, progress towards development of rigorous frameworks to represent and analyze this phenomenon has been limited. In this paper, we present results that move towards addressing this problem. Specifically, we show how the emergent semantics of a data collection can be first formalized and then captured and represented using network models across users. Using real-world data from a group of users, we then show how such networks can be theoretically characterized and highlight many of their important properties. The primary results communicated in this paper include: (1) a graph-theoretic approach for formalization of the notion of emergent semantics, (2) description of how real-world emergent semantics can be captured and represented as networks, and (3) investigation of the issue of quantitative characterization of emergent semantics through the analysis of these networks.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114084963","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: 0
Sill Image Object Categorization Using 2D Objects Models 使用2D对象模型的静止图像对象分类
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.22
Raluca-Diana Sambra-Petre, T. Zaharia
{"title":"Sill Image Object Categorization Using 2D Objects Models","authors":"Raluca-Diana Sambra-Petre, T. Zaharia","doi":"10.1109/ICSC.2011.22","DOIUrl":"https://doi.org/10.1109/ICSC.2011.22","url":null,"abstract":"This paper proposes a novel recognition scheme for semantic labeling of 2D objects present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to associate the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Experiments show that such a system can achieve recognition rate up to 70.4%.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126916580","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
PhishZoo: Detecting Phishing Websites by Looking at Them PhishZoo:通过观察来检测钓鱼网站
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.52
Sadia Afroz, R. Greenstadt
{"title":"PhishZoo: Detecting Phishing Websites by Looking at Them","authors":"Sadia Afroz, R. Greenstadt","doi":"10.1109/ICSC.2011.52","DOIUrl":"https://doi.org/10.1109/ICSC.2011.52","url":null,"abstract":"Phishing is a security attack that involves obtaining sensitive or otherwise private data by presenting oneself as a trustworthy entity. Phishers often exploit users' trust on the appearance of a site by using web pages that are visually similar to an authentic site. This paper proposes a phishing detection approach -- PhishZoo -- that uses profiles of trusted websites' appearances to detect phishing. Our approach provides similar accuracy to blacklisting approaches (96%), with the advantage that it can classify zero-day phishing attacks and targeted attacks against smaller sites (such as corporate intranets). A key contribution of this paper is that it includes a performance analysis and a framework for making use of computer vision techniques in a practical way.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124212409","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: 175
Automated Profiling of the Balance of Optimism and Pessimism in Online News Content 在线新闻内容中乐观与悲观平衡的自动分析
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.85
T. Musgrove, Robin Walsh, Peter Ridge
{"title":"Automated Profiling of the Balance of Optimism and Pessimism in Online News Content","authors":"T. Musgrove, Robin Walsh, Peter Ridge","doi":"10.1109/ICSC.2011.85","DOIUrl":"https://doi.org/10.1109/ICSC.2011.85","url":null,"abstract":"Using semantic techniques, we determined a probabilistic score indicating whether news stories were more optimistic (or solutions-oriented), versus their being more pessimistic (or threnodic). We observed over the length of our study that some news outlets, which were comparable in their topical coverage, quantity of output, and geographical focus, differed vastly in their level of optimistic or solutions-oriented news content. This did not seem to correlate with any perceived political bias (left vs. right) nor with the demographic of the target audience, and so raises questions of whether editorial culture or some other causal factor is at work, apart from the typical ideological or audience-driven biases. We found that it is indeed possible on a fully automated basis to profile media sources as falling more on the optimistic or pessimistic side of the spectrum.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125143559","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: 0
Dynamic Discovery of Complex Constraint-Based Semantic Web Services 基于约束的复杂语义Web服务动态发现
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.38
Le Duy Ngan, L. Jie, K. Rajaraman
{"title":"Dynamic Discovery of Complex Constraint-Based Semantic Web Services","authors":"Le Duy Ngan, L. Jie, K. Rajaraman","doi":"10.1109/ICSC.2011.38","DOIUrl":"https://doi.org/10.1109/ICSC.2011.38","url":null,"abstract":"Web service discovery is the process of finding web service providers that satisfy specific service requester requirements. In real life scenarios, services are often described with complex constraints and contain dynamic aspects that are not adequately supported by most of the current discovery systems. In this paper, we propose a novel OWL-S based semantic service discovery system for dynamically discovering complex constraint-based services. The proposed system is based on representing complex service constraints as Semantic Web Rule Language (SWRL) rules and using a rule engine for matchmaking, and handling dynamism via a real-time ontology population and reasoning infrastructure. We consider the Semantic Web Service (SWS) Challenge shipping discovery scenario, and show with detailed illustration that our system is able to solve all the five service complexity levels successfully.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114325893","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: 13
Transforming XML Schema to OWL Using Patterns 使用模式将XML模式转换为OWL
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.77
Ivan Bedini, C. Matheus, P. Patel-Schneider, Aidan Boran, B. Nguyen
{"title":"Transforming XML Schema to OWL Using Patterns","authors":"Ivan Bedini, C. Matheus, P. Patel-Schneider, Aidan Boran, B. Nguyen","doi":"10.1109/ICSC.2011.77","DOIUrl":"https://doi.org/10.1109/ICSC.2011.77","url":null,"abstract":"One of the promises of the Semantic Web is to support applications that easily and seamlessly deal with heterogeneous data. Most data on the Web, however, is in the Extensible Markup Language (XML) format, but using XML requires applications to understand the format of each data source that they access. To achieve the benefits of the Semantic Web involves transforming XML into the Semantic Web language, OWL (Ontology Web Language), a process that generally has manual or only semi-automatic components. In this paper we present a set of patterns that enable the direct, automatic transformation from XML Schema into OWL allowing the integration of much XML data in the Semantic Web. We focus on an advanced logical representation of XML Schema components and present an implementation, including a comparison with related work.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128237765","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: 61
Semantic Annotation of Street-Level Geospatial Entities 街道级地理空间实体的语义标注
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.53
Nate Blaylock
{"title":"Semantic Annotation of Street-Level Geospatial Entities","authors":"Nate Blaylock","doi":"10.1109/ICSC.2011.53","DOIUrl":"https://doi.org/10.1109/ICSC.2011.53","url":null,"abstract":"In this paper, we describe the PURSUIT Corpus -- an annotated corpus of geospatial path descriptions in spoken natural language. PURSUIT includes the spoken path descriptions along with a synchronized GPS track of the path actually taken. Additionally, we have manually annotated geospatial entity mentions in PURSUIT, mapping them onto point entries in several geographic information system databases. PURSUIT has been made freely available for download.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129013904","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: 7
SBA-term: Sparse Bilingual Association for Terms sba术语:术语的稀疏双语关联
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.25
Xinyu Dai, Jinzhu Jia, L. Ghaoui, Bin Yu
{"title":"SBA-term: Sparse Bilingual Association for Terms","authors":"Xinyu Dai, Jinzhu Jia, L. Ghaoui, Bin Yu","doi":"10.1109/ICSC.2011.25","DOIUrl":"https://doi.org/10.1109/ICSC.2011.25","url":null,"abstract":"Bilingual semantic term association is very useful in cross-language information retrieval, statistical machine translation, and many other applications in natural language processing. In this paper, we present a method, named SBA-term, which applies sparse linear regression (Lasso, Least Squares with l1 penalty) and L2 rescaling for design matrix to the task of bilingual term association. The approach hinges on formulating the task as a feature selection problem within a classification framework. Our experimental results indicate that our novel proposed method is more efficient than co-occurrence at extracting relevant bilingual terms semantic associations. In addition, our approach connects the vibrant area of sparse machine learning to an important problem of natural language processing.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116351206","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
Semantic Models for Style-Based Text Clustering 基于样式的文本聚类语义模型
2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI: 10.1109/ICSC.2011.24
A. Leoncini, Fabio Sangiacomo, C. Peretti, Sonia Argentesi, R. Zunino, E. Cambria
{"title":"Semantic Models for Style-Based Text Clustering","authors":"A. Leoncini, Fabio Sangiacomo, C. Peretti, Sonia Argentesi, R. Zunino, E. Cambria","doi":"10.1109/ICSC.2011.24","DOIUrl":"https://doi.org/10.1109/ICSC.2011.24","url":null,"abstract":"The paper addresses some roles of concept-based representations in document clustering to support knowledge discovery. Computational Intelligence algorithms can benefit from semantic networks in the definition of similarity between pairs of documents. After analyzing the tuning of semantic networks in a systematic fashion, the research defines and evaluates a novel semantic-based metrics, which integrates both classical and style-related features of texts. Experimental results confirm the effectiveness of the approach, showing that applying a refined semantic representation into a clustering engine yields consistent structures for information retrieval and knowledge acquisition.","PeriodicalId":408382,"journal":{"name":"2011 IEEE Fifth International Conference on Semantic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115002959","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: 4
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