Combining Word Embedding and Lexical Database for Semantic Relatedness Measurement

scientific article published in 2016

Combining Word Embedding and Lexical Database for Semantic Relatedness Measurement is …
instance of (P31):
scholarly articleQ13442814

External links are
P3332ACM Digital Library citation ID2872518.2889395
P8978DBLP publication IDconf/www/LeeKHC16a
P356DOI10.1145/2872518.2889395

P2093author name stringHao Ke
Hen-Hsen Huang
Hsin-Hsi Chen
Yang-Yin Lee
P2860cites workGloVe: Global Vectors for Word RepresentationQ22827276
Distributed Representations of Words and Phrases and their CompositionalityQ24731579
Placing search in context: the concept revisitedQ28045598
Multimodal distributional semanticsQ43974940
Contextual correlates of synonymyQ43976276
Measuring semantic similarity in the taxonomy of WordNetQ55258805
SensEmbed: Learning Sense Embeddings for Word and Relational SimilarityQ55259488
P4510describes a project that usesWord2vecQ22673982
GloVeQ22826110
WordSim-353Q31845205
MEN Test CollectionQ43978931
Rubenstein-Goodenough datasetQ43981247
YP130Q55259916
P921main subjectword embeddingQ18395344
databaseQ8513
P304page(s)73-74
P577publication date2016-01-01
P1433published inProceedings of the 25th International Conference Companion on World Wide WebQ41778545
P1476titleCombining Word Embedding and Lexical Database for Semantic Relatedness Measurement

Reverse relations

Q87133557Creating Semantic Representationscites workP2860

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