Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)最新文献_第2页

Enriching mobile semantic search with web services 用web服务丰富移动语义搜索

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050850

Minjae Song, Sungkwang Eom, Sangjin Shin, Kyong-Ho Lee

{"title":"Enriching mobile semantic search with web services","authors":"Minjae Song, Sungkwang Eom, Sangjin Shin, Kyong-Ho Lee","doi":"10.1109/ICOSC.2015.7050850","DOIUrl":"https://doi.org/10.1109/ICOSC.2015.7050850","url":null,"abstract":"With the increasing number of mobile devices, there have been many researches on searching and managing a large volume of mobile data. Most of the mobile platforms today provide users with keyword-based full text search (FTS) in order to search for mobile data. Recently, voice search interfaces have been deployed. These search methods, however, query only the keywords given as an input to local databases in mobile devices. Therefore, it is quite difficult to figure out and to provide what a user really wants. To overcome this limitation, we propose a semantic search method for mobile platforms. The proposed method augments the results of semantic search on local databases with their related useful Web information according to the intention and context information of a user. Although there are various semantic search techniques, it is hard to apply the existing methods to mobile devices due to the characteristics of mobile devices such as isolated database structures and limited computing resources. To enable semantic search on mobile devices, we also propose a lightweight mobile ontology. The proposed mobile ontology is also aligned with related Web information to enrich search results. Experimental results from prototype implementation of the proposed method verify that our approach provides more accurate results than the conventional FTS does. In addition, the proposed method shows an acceptable amount of response time and battery consumption.","PeriodicalId":126701,"journal":{"name":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122157489","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

SemRank: Semantic rank learning for multimedia retrieval 语义秩:多媒体检索的语义秩学习

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050778

David Etter, C. Domeniconi

{"title":"SemRank: Semantic rank learning for multimedia retrieval","authors":"David Etter, C. Domeniconi","doi":"10.1109/ICOSC.2015.7050778","DOIUrl":"https://doi.org/10.1109/ICOSC.2015.7050778","url":null,"abstract":"Multimedia retrieval suffers from the lack of common feature representation between a text based query and the visual content of a video repository. One approach to bridging this representation gap is known as query-by-concept, where a query and video are mapped into a common semantic feature space. One of the challenges with using semantic concepts for multimedia retrieval, is that the available vocabulary size is generally not sufficient for representing the content of the query and video. In addition, the lack of training data and visual feature representation often leads to low precision models. In this work, we explore the use of a query-by-concept approach for the multimedia Known Item Search (KIS) problem. We propose a semantic rank learning model, called SemRank, to overcome the challenges of the vocabulary size and lack of training data. First, we construct a semantic fusion model to combine the output from many noisy classifiers. Next, we train a gradient boosted regression tree model, using a semantic feature space derived from the query, video, and query-video similarity. Our approach is evaluated over a large internet video repository, and the results show that query-by-concept can be an effective model for multimedia KIS.","PeriodicalId":126701,"journal":{"name":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127805088","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

Linked crowdsourced data - Enabling location analytics in the linking open data cloud 链接的众包数据——在链接的开放数据云中启用位置分析

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050776

A. Uzun

引用次数: 1

Advertising slogan generation system reflecting user preference on the web 反映网络用户偏好的广告语生成系统

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050834

Hiroaki Yamane, M. Hagiwara

{"title":"Advertising slogan generation system reflecting user preference on the web","authors":"Hiroaki Yamane, M. Hagiwara","doi":"10.1109/ICOSC.2015.7050834","DOIUrl":"https://doi.org/10.1109/ICOSC.2015.7050834","url":null,"abstract":"Increased demand for Web advertising has resulted in a corresponding increase in the need to develop online personalized advertisements. This paper proposes an advertising-slogan generation system reflecting Web-user preferences. Using a social networking service (SNS) site as the knowledge base for word preferences, and by employing an advertising slogan corpus, the proposed system aims to generate slogans that reflect advertising posts on an SNS. Using model slogans selected from a corpus containing 24,472 slogans, the proposed system generates slogan candidates using the knowledge obtained from a post on an SNS. These slogan candidates are selected based on the following three indexes: the natural level given by a large-scale balanced corpus, a semantic-relations score using advertising slogans, and the preference level obtained from SNS sites. In particular, the proposed system extracts preference data from these SNS fan pages and estimates the preference level on each word based on a bag-of-words model. This enables the proposed system to select slogans in a timely fashion. The authors conducted a subjective experiment to examine the quality of the generated slogans. The results show that (1) the natural and semantic-relation levels are effective for selecting slogans that reflect a post, and (2) the preference-level index contributes to the selection of preferred slogans that are interesting to users.","PeriodicalId":126701,"journal":{"name":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126801528","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

Partitioning of ontologies driven by a structure-based approach 由基于结构的方法驱动的本体划分

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/icosc.2015.7050827

F. Amato, Aniello De Santo, V. Moscato, Fabio Persia, A. Picariello, S. Poccia

引用次数: 19

Schema adaptive modeling and incremental matching for web interface web界面模式自适应建模与增量匹配

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050804

Heng Chen, Hai Jin, Feng Zhao, Lei Zhu

{"title":"Schema adaptive modeling and incremental matching for web interface","authors":"Heng Chen, Hai Jin, Feng Zhao, Lei Zhu","doi":"10.1109/ICOSC.2015.7050804","DOIUrl":"https://doi.org/10.1109/ICOSC.2015.7050804","url":null,"abstract":"There are so many web data hidden behind so-called deep web and can only be accessed through query interfaces, and the data volume is increasing. We often need to fill forms over alternative interfaces in the same domain to select the best product or service, such as buying a book across various online book websites to choose the most affordable one. Integrating these web interfaces in the same domain to an uniform interface is as a matter of course. One of the most important things for interface integration is interface schema matching. In this paper, we present a new structure and a corresponding algorithm for web interface schema modeling and matching. Using the new schema structure, we could not only easily handle two interfaces schema matching, but also handle incremental schema matching between an existing integrated interface and a new interface. We present a detailed experimental evaluation using UIUC Web Integration Repository dataset. The results show that our approach is effective: it obtains significantly higher accuracy for two schema matching and is more robust than previous techniques. For incremental schema matching, it also performs well.","PeriodicalId":126701,"journal":{"name":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121029879","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

Weighted finite automata based on local patterns for image authentication 基于局部模式的图像认证加权有限自动机

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050797

U. Raju, Shibin George, Irlanki Sandeep, Kothuri Sai Kiran

引用次数: 2

Semantic description, discovery and integration for the Internet of Things 物联网的语义描述、发现和集成

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050819

Sejin Chun, Seungmin Seo, Byungkook Oh, Kyong-Ho Lee

引用次数: 43

Cascade object detection with complementary features and algorithms 具有互补特征和算法的级联目标检测

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050775

De Cheng, Jinjun Wang, Xing Wei, Nan Liu, Shizhou Zhang, Yihong Gong, N. Zheng

{"title":"Cascade object detection with complementary features and algorithms","authors":"De Cheng, Jinjun Wang, Xing Wei, Nan Liu, Shizhou Zhang, Yihong Gong, N. Zheng","doi":"10.1109/ICOSC.2015.7050775","DOIUrl":"https://doi.org/10.1109/ICOSC.2015.7050775","url":null,"abstract":"This paper presents a novel method of combining the object detection algorithms and the methods used for image classification aiming to further boosting the object detection performance. Since the algorithm and image features which used in the image classification tasks have not been well transplanted into the object detection method, most of the reason is that the feature used in the image classification is extracted from the whole image which have no space information. In our framework, firstly we use the detection model to propose the candidate windows; in the second stage the candidate windows will act as the whole image to be classified. Intuitively, the first stage should have high recall, while the second stage should have high precision. In our proposed detection framework, a SVM model was trained to combine the scores computed from both stages. The proposed framework can be generally used, while in our experiments we used the LSVM as the object detector in the first stage and the mostly used deep convolutional neural network classifier in the second stage. Finally, a combined model shows that the object detection performance can be further boosted under this framework in our experiments.","PeriodicalId":126701,"journal":{"name":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130887646","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

NNB: An efficient nearest neighbor search method for hierarchical clustering on large datasets NNB:一种高效的大数据集分层聚类的最近邻搜索方法

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-03-02 DOI: 10.1109/ICOSC.2015.7050840

Wei Zhang, Gongxuan Zhang, Yongli Wang, Zhaomeng Zhu, Tao Li

引用次数: 9