Name
Abstract | ||
|---|---|---|
Document similarity is basic for Information Retrieval. Cross Lingual (CL) similarity is important for many data processing tasks such as CL palgiarism detection and retrieval and document quality assessment. We study CL similarity based on the Explicit Semantic Association (ESA) adapted to a cross lingual setting with focus on Arabic. We compare the degree to which CL similarity testing performs where one of the language is Arabic with its monolingual counterpart for various text chunk sizes. We describe the used infrastructure and report on some of the testing results, study the possible sources of encountered weaknesses and point to the possible directions for improvement. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-73500-9_10 | Communications in Computer and Information Science |
Keywords | DocType | Volume |
Cross lingual information retrieval,Document similarity Explicit Semantic Association,CL-ESA,Arabic information retrieval | Conference | 782 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Salhi | 1 | 1 | 0.69 |
| Adnan H. Yahya | 2 | 0 | 0.34 |