Mosab Faqeeh, M. Al-Ayyoub, Mohammad Wardat, Ismail Hmeidi, Y. Jararweh
{"title":"物联网主题搜索引擎","authors":"Mosab Faqeeh, M. Al-Ayyoub, Mohammad Wardat, Ismail Hmeidi, Y. Jararweh","doi":"10.1109/AICCSA.2014.7073287","DOIUrl":null,"url":null,"abstract":"Internet of Things (IoT) has become a common buzzword nowadays in the Web. However, there is no search tool currently in place for discovering and learning about the different types of IoT elements. Hence, this paper presents a topical search engine for IoT. The motivation for a topical search engine comes from the relatively poor performance of general-purpose search engines, which depend on the results of generic Web crawlers. The topical search engine is a system that learns the specialization from examples, and then explores the Web, guided by a relevance and popularity rating mechanism. The results show that the proposed topical search engine outperforms other general search engines.","PeriodicalId":412749,"journal":{"name":"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Topical search engine for Internet of Things\",\"authors\":\"Mosab Faqeeh, M. Al-Ayyoub, Mohammad Wardat, Ismail Hmeidi, Y. Jararweh\",\"doi\":\"10.1109/AICCSA.2014.7073287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Internet of Things (IoT) has become a common buzzword nowadays in the Web. However, there is no search tool currently in place for discovering and learning about the different types of IoT elements. Hence, this paper presents a topical search engine for IoT. The motivation for a topical search engine comes from the relatively poor performance of general-purpose search engines, which depend on the results of generic Web crawlers. The topical search engine is a system that learns the specialization from examples, and then explores the Web, guided by a relevance and popularity rating mechanism. The results show that the proposed topical search engine outperforms other general search engines.\",\"PeriodicalId\":412749,\"journal\":{\"name\":\"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICCSA.2014.7073287\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2014.7073287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Internet of Things (IoT) has become a common buzzword nowadays in the Web. However, there is no search tool currently in place for discovering and learning about the different types of IoT elements. Hence, this paper presents a topical search engine for IoT. The motivation for a topical search engine comes from the relatively poor performance of general-purpose search engines, which depend on the results of generic Web crawlers. The topical search engine is a system that learns the specialization from examples, and then explores the Web, guided by a relevance and popularity rating mechanism. The results show that the proposed topical search engine outperforms other general search engines.