Name
Title | ||
|---|---|---|
Microblog semantic context retrieval system based on linked open data and graph-based theory. |
Abstract | ||
|---|---|---|
•We present a novel information retrieval system for context similarity retrieval in microblogging platforms.•We present a method for extracting and linking entities to DBpedia concepts.•We contextualize all matched concepts using graph centrality property by defining a new weighting factor.•We present two algorithms which perform the semantic similarity by considering the weight of concepts and their related concepts.•We use a real Twitter dataset to show the effectiveness of our system. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.eswa.2016.01.020 | Expert Systems with Applications |
Keywords | Field | DocType |
Information retrieval,Semantic similarity,Linked open data,DBpedia,Named entity linking,Graph centrality | Semantic similarity,Data mining,Social media,Information retrieval,Similarity measure,Computer science,Microblogging,Semantic gap,Centrality,Linked data,Knowledge base,Semantics | Journal |
Volume | Issue | ISSN |
53 | C | 0957-4174 |
Citations | PageRank | References |
5 | 0.41 | 34 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fahd Kalloubi | 1 | 13 | 2.23 |
| El Habib Nfaoui | 2 | 15 | 6.44 |
| Omar El Beqqali | 3 | 23 | 7.59 |