2015
DOI: 10.1007/978-3-319-25210-0_17
|View full text |Cite
|
Sign up to set email alerts
|

Combining Semantic Query Disambiguation and Expansion to Improve Intelligent Information Retrieval

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2017
2017
2023
2023

Publication Types

Select...
2
2
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 23 publications
0
2
0
Order By: Relevance
“…In addition, the synset in WordNet can be formulized as . The term weight in and are set as 1, and the term weight in are calculated as formula (1). The similarity between and determines which concept term mapped to, which can be described as below:…”
Section: Mapping Conceptsmentioning
confidence: 99%
See 1 more Smart Citation
“…In addition, the synset in WordNet can be formulized as . The term weight in and are set as 1, and the term weight in are calculated as formula (1). The similarity between and determines which concept term mapped to, which can be described as below:…”
Section: Mapping Conceptsmentioning
confidence: 99%
“…In the information retrieval field, there exists some serious semantic problem because of the following two facts, (1) the document indexers and the users' queries may be not the same words but with closely related senses; (2) queries and documents terms can have multiple senses which may lead to sense ambiguity problem [1,2]. It is known as the vocabulary problems, compounded by synonym (different words with similar meaning) and polysemy (a word with different meanings) [3].…”
Section: Introductionmentioning
confidence: 99%