2011 International Conference on Semantic Technology and Information Retrieval最新文献_第4页

An Interactive Malaysia Crime News Retrieval System 交互式马来西亚犯罪新闻检索系统

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995792

M. Mohd, Nazlena Mohamad Ali

引用次数: 5

Dynamic ontology editor for a knowledge management system of scholarly activities 动态本体编辑器用于学术活动的知识管理系统

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995758

M. Ismail, R. G. Raj, S. A. Kareem

引用次数: 3

Construction of topics and clusters in Topic Detection and Tracking tasks 主题检测与跟踪任务中主题与聚类的构建

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995784

M. Mohd, F. Crestani, I. Ruthven

引用次数: 5

Measuring flow in gaming platforms 衡量游戏平台的流量

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995806

A. Omar, Nazlena Mohamad Ali

引用次数: 10

An early stage of knowledge acquisition based on Quranic text 基于古兰经文本的早期知识获取阶段

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995777

S. Saad, N. Salim, Suhaila Zainuddin

引用次数: 14

A collaborative names recommendation in the Twitter environment based on location 基于位置的Twitter环境中的协作名称推荐

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995775

N. Jamil, A. Alhadi, S. Noah

{"title":"A collaborative names recommendation in the Twitter environment based on location","authors":"N. Jamil, A. Alhadi, S. Noah","doi":"10.1109/STAIR.2011.5995775","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995775","url":null,"abstract":"Friendster, Facebook, Twitter and many other microblogs have been introduced since 2004. These web 2.0 applications have become a powerful tool for communication. Each social web site has millions of users whose interact with each other regardless of their location and distance. Therefore, the mechanism of recommendation system for these sites is important for users to find suitable friends. Name recommendation should be made based on the concept of homophily which stated that relationships between individuals who have in common is higher than individuals who have nothing in common. Twitter is one of the popular social web sites that were developed in 2006. Many of the Twitter users are passive users. They just follow other users but on the other side they do not have many followers. This problem arises because reciprocal relationship is not required in Twitter. To overcome this problem, a recommendation system can help users in searching friends by taking into account reciprocal relationships. The main goal of this study is to use collaborative filtering techniques to recommend names based on geographical location. User's location is taken from the user's profile by using coordinates of latitude and longitude. Celebrities profile data sets provided by the Korea Advanced Institute of Science and Technology (KAIST) are taken for testing purposes. The result of the testing indicates the potential of exploiting geographical locations in collaboratively recommending names within Twitter environment.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128782143","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

Modeling semantic correspondence in heterogeneous structured document collection 异构结构化文档集合中的语义对应建模

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995787

Saravadee Sae Tan, E. Tang, Bali Ranaivo-Malançon, G. Sodhy

{"title":"Modeling semantic correspondence in heterogeneous structured document collection","authors":"Saravadee Sae Tan, E. Tang, Bali Ranaivo-Malançon, G. Sodhy","doi":"10.1109/STAIR.2011.5995787","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995787","url":null,"abstract":"On the web, most structured document collections consist of documents from different sources and marked up with different types of structures. The diversity of structures has led to the emergence of heterogeneous structured documents. The heterogeneity of structured documents is one of the reason for query-document mismatch in structured document retrieval. In structured document retrieval, a user is assumed to have intimate knowledge of the document structures and is able to specify contextual constraints in their queries. However, it is impossible for the user to know all structures in heterogeneous structured document collections. In this paper, we propose to include similar correspondence relations in the representation model for structured document retrieval. The similar correspondences make the relations between similar contents explicit in order to improve structured document retrieval effectiveness. We introduce a generic and flexible structured document model to represent heterogeneous structured documents as well as the similar correspondences in the document collections. We also illustrate how the proposed model can be utilized in structured document retrieval.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"161 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125946652","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

Extraction of academic social network from online database 从在线数据库中提取学术社交网络

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995766

M. K. Nasution, S. Noah

引用次数: 44

Using Latent Semantic Analysis for automated grading programming assignments 使用潜在语义分析自动评分编程作业

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995769

Kartinah Zen, D. A. Iskandar, Ongkir Linang

引用次数: 15

A framework for integrating DBpedia in a multi-modality ontology news image retrieval system 一个将DBpedia集成到多模态本体新闻图像检索系统中的框架

2011 International Conference on Semantic Technology and Information Retrieval Pub Date : 2011-06-28 DOI: 10.1109/STAIR.2011.5995779

Yanti Idaya Aspura Mohd Khalid, S. Noah

{"title":"A framework for integrating DBpedia in a multi-modality ontology news image retrieval system","authors":"Yanti Idaya Aspura Mohd Khalid, S. Noah","doi":"10.1109/STAIR.2011.5995779","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995779","url":null,"abstract":"Knowledge sharing communities like Wikipedia and automated extraction like DBpedia enable a large construction of machine processing knowledge bases with relational fact of entities. These options give a great opportunity for researcher to use it as a domain concept between low-level features and high-level concepts for image retrieval. The collection of images attached to entities, such as on-line news articles with images, are abundant on the Internet. Still, it is difficult to retrieve accurate information on these entities. Using entity names in a search engine yields large lists, but often results in imprecise and unsatisfactory outcomes. Our goal is to populate a knowledge base with on-line image news resources in the BBC sport domain. This system will yield high precision, a high recall and include diverse sports photos for specific entities. A multi-modality ontology retrieval system, with relational facts about entities for generating expanded queries, will be used to retrieve results. DBpedia will be used as a domain sport ontology description, and will be integrated with a textual description and a visual description, both generated by hand. To overcome semantic interoperability between ontologies, automated ontology alignment is used. In addition, visual similarity measures based on MPEG7 descriptions and SIFT features, are used for higher diversity in the final rankings.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890692","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: 16