{"title":"GPU加速用户生成内容的热词提取","authors":"Ming Cheng, K. F. Chung, S. Chuang","doi":"10.1109/WAINA.2012.147","DOIUrl":null,"url":null,"abstract":"In this paper, a GPU based hot term extraction algorithm is presented. Graphics Processing Units (GPUs) is designed for data-parallel computations. Comparing to running a single program with multiple data in CPU, GPU can have faster execution. The hot term is defined as a word that appears frequently in the search result. We assume that the greater the frequency of appearance of a term, the more the relevancy of the term to the users. As there are lots of terms in the searched results from user generated content (UGC), processing them is time-consuming. The proposed GPU based hot term extraction algorithm can achieve a fast performance and works well in real-time applications.","PeriodicalId":375709,"journal":{"name":"2012 26th International Conference on Advanced Information Networking and Applications Workshops","volume":"58 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"GPU Accelerated Hot Term Extraction from User Generated Content\",\"authors\":\"Ming Cheng, K. F. Chung, S. Chuang\",\"doi\":\"10.1109/WAINA.2012.147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a GPU based hot term extraction algorithm is presented. Graphics Processing Units (GPUs) is designed for data-parallel computations. Comparing to running a single program with multiple data in CPU, GPU can have faster execution. The hot term is defined as a word that appears frequently in the search result. We assume that the greater the frequency of appearance of a term, the more the relevancy of the term to the users. As there are lots of terms in the searched results from user generated content (UGC), processing them is time-consuming. The proposed GPU based hot term extraction algorithm can achieve a fast performance and works well in real-time applications.\",\"PeriodicalId\":375709,\"journal\":{\"name\":\"2012 26th International Conference on Advanced Information Networking and Applications Workshops\",\"volume\":\"58 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 26th International Conference on Advanced Information Networking and Applications Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WAINA.2012.147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 26th International Conference on Advanced Information Networking and Applications Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WAINA.2012.147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GPU Accelerated Hot Term Extraction from User Generated Content
In this paper, a GPU based hot term extraction algorithm is presented. Graphics Processing Units (GPUs) is designed for data-parallel computations. Comparing to running a single program with multiple data in CPU, GPU can have faster execution. The hot term is defined as a word that appears frequently in the search result. We assume that the greater the frequency of appearance of a term, the more the relevancy of the term to the users. As there are lots of terms in the searched results from user generated content (UGC), processing them is time-consuming. The proposed GPU based hot term extraction algorithm can achieve a fast performance and works well in real-time applications.