{"title":"面向商业大数据的语义社会网络分析","authors":"W. Du","doi":"10.1109/SKG.2018.00050","DOIUrl":null,"url":null,"abstract":"This paper first presents results of our three recent research projects on using social network analysis (SNA) techniques to analyze business big data involving stock data, trading data, and business contract data. The analysis on historical stock data identifies alternative representative indexing stock groups. The analysis on high frequency trading data establishes new algorithms for more effective high frequency trading. The analysis on business contract networks studies relationships between companies' contracts and their performance in profits and stock levels. The paper then discusses approaches to incorporating explicit semantics into conventional social networks and extending standard social network analysis techniques to more effective semantics-based analysis.","PeriodicalId":265760,"journal":{"name":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Toward Semantic Social Network Analysis for Business Big Data\",\"authors\":\"W. Du\",\"doi\":\"10.1109/SKG.2018.00050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper first presents results of our three recent research projects on using social network analysis (SNA) techniques to analyze business big data involving stock data, trading data, and business contract data. The analysis on historical stock data identifies alternative representative indexing stock groups. The analysis on high frequency trading data establishes new algorithms for more effective high frequency trading. The analysis on business contract networks studies relationships between companies' contracts and their performance in profits and stock levels. The paper then discusses approaches to incorporating explicit semantics into conventional social networks and extending standard social network analysis techniques to more effective semantics-based analysis.\",\"PeriodicalId\":265760,\"journal\":{\"name\":\"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SKG.2018.00050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SKG.2018.00050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Toward Semantic Social Network Analysis for Business Big Data
This paper first presents results of our three recent research projects on using social network analysis (SNA) techniques to analyze business big data involving stock data, trading data, and business contract data. The analysis on historical stock data identifies alternative representative indexing stock groups. The analysis on high frequency trading data establishes new algorithms for more effective high frequency trading. The analysis on business contract networks studies relationships between companies' contracts and their performance in profits and stock levels. The paper then discusses approaches to incorporating explicit semantics into conventional social networks and extending standard social network analysis techniques to more effective semantics-based analysis.