Name
Abstract | ||
|---|---|---|
One key issue in text mining and natural language processing is how to effectively represent documents using numerical vectors. One classical model is the Bag-of-Words (BoW). In a BoW-based vector representation of a document, each element denotes the normalized number of occurrence of a basis term in the document. To count the number of occurrence of a basis term, BoW conducts exact word matching... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TFUZZ.2017.2690222 | IEEE Transactions on Fuzzy Systems |
Keywords | Field | DocType |
Semantics,Dogs,Computational modeling,Text mining,Vocabulary,Analytical models,Numerical models | Document classification,String searching algorithm,Bag-of-words model,Cosine similarity,Computer science,Fuzzy logic,Artificial intelligence,Natural language processing,Vocabulary,Semantics,Semantic matching | Journal |
Volume | Issue | ISSN |
26 | 2 | 1063-6706 |
Citations | PageRank | References |
13 | 0.61 | 22 |
Authors | ||
2 | ||