Semantic Measures: How Similar? How Related?

被引:1
作者
Costa, Teresa [1 ]
Leal, Jose Paulo
机构
[1] Univ Porto, Fac Sci, CRACS, Oporto, Portugal
来源
WEB ENGINEERING (ICWE 2016) | 2016年 / 9671卷
关键词
Semantic similarity; Semantic relatedness; Semantic measures; Linked data; CONTEXT;
D O I
10.1007/978-3-319-38791-8_29
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There are two main types of semantic measures (SM): similarity and relatedness. There are also two main types of datasets, those intended for similarity evaluations and those intended for relatedness. Although they are clearly distinct, they are similar enough to generate some misconceptions. Is there a confusion between similarity and relatedness among the semantic measure community, both the designers of SMs and the creators of benchmarks? This is the question that the research presented in this paper tries to answer. Authors performed a survey of both the SMs and datasets and executed a cross evaluation of those measures and datasets. The results show different consistency of measures with datasets of the same type. This research enabled us to conclude not only that there is indeed some confusion but also to pinpoint the SMs and benchmarks less consistent with their intended type.
引用
收藏
页码:431 / 438
页数:8
相关论文
共 20 条
[1]  
Agirre E, 2009, PROC N AM CHAPTER AS
[2]  
[Anonymous], ARXIV14083456
[3]  
[Anonymous], 1994, P 32 ANN M ASS COMP
[4]  
[Anonymous], 1999, WordNet
[5]  
[Anonymous], 1998, ICML
[6]  
Bodenreider O., 2005, PACIFIC S BIOCOMPUTI
[7]   Multimodal Distributional Semantics [J].
Bruni, Elia ;
Nam Khanh Tran ;
Baroni, Marco .
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2014, 49 :1-47
[8]  
Budanitsky A, 2006, COMPUT LINGUIST, V32, P13, DOI 10.1162/coli.2006.32.1.13
[9]  
Evgeniy G., WORDSIMILARITY 353 T
[10]  
Gorodnichenko Y., 2012, I COMP EC DEV, V150, P213