{"title":"考虑多重关系的汉语类比检索","authors":"Chao Liang, Zhao Lu","doi":"10.1109/CSC.2012.37","DOIUrl":null,"url":null,"abstract":"There are some specific relations between the entities of the nature. The same relationship exists between two pairs of entities, simply to say, what A is to B as C is to D. For two unfamiliar entities (A, B), We cannot say precisely the relationship between them. When given an instance C similar to A, we cannot say out the entity D corresponding to B. Latent relation search provides a new way of searching D after given the question (A, B) and (C, ?). This paper proposed a Latent relation search method based on words frequency and weight of words. We explore all the relations between entity A and B by using K-means clustering method and then determine entity D corresponding to C in different relationship types. The proposed method achieves an MRR of 0.773.","PeriodicalId":183800,"journal":{"name":"2012 International Conference on Cloud and Service Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Chinese Analogy Search Considering Multi Relations\",\"authors\":\"Chao Liang, Zhao Lu\",\"doi\":\"10.1109/CSC.2012.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are some specific relations between the entities of the nature. The same relationship exists between two pairs of entities, simply to say, what A is to B as C is to D. For two unfamiliar entities (A, B), We cannot say precisely the relationship between them. When given an instance C similar to A, we cannot say out the entity D corresponding to B. Latent relation search provides a new way of searching D after given the question (A, B) and (C, ?). This paper proposed a Latent relation search method based on words frequency and weight of words. We explore all the relations between entity A and B by using K-means clustering method and then determine entity D corresponding to C in different relationship types. The proposed method achieves an MRR of 0.773.\",\"PeriodicalId\":183800,\"journal\":{\"name\":\"2012 International Conference on Cloud and Service Computing\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Cloud and Service Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSC.2012.37\",\"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 International Conference on Cloud and Service Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSC.2012.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chinese Analogy Search Considering Multi Relations
There are some specific relations between the entities of the nature. The same relationship exists between two pairs of entities, simply to say, what A is to B as C is to D. For two unfamiliar entities (A, B), We cannot say precisely the relationship between them. When given an instance C similar to A, we cannot say out the entity D corresponding to B. Latent relation search provides a new way of searching D after given the question (A, B) and (C, ?). This paper proposed a Latent relation search method based on words frequency and weight of words. We explore all the relations between entity A and B by using K-means clustering method and then determine entity D corresponding to C in different relationship types. The proposed method achieves an MRR of 0.773.