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Information Retrieval using Cosine and Jaccard Similarity Measures in Vector Space Model
| Content Provider | Semantic Scholar |
|---|---|
| Author | Jain, Abhishek Jain, Aman Chauhan, Nihal Singh, Vikrant Thakur, Narina |
| Copyright Year | 2017 |
| Abstract | With the exponential growth of documents available to us on the web, the requirement for an effective technique to retrieve the most relevant document matching a given search query has become critical. The field of Information Retrieval deals with the problem of document similarity to retrieve desired information from a large amount of data. Various models and similarity measures have been proposed to determine the extent of similarity between two objects. The objective of this paper is to summarize the entire process, looking into some of the most well-known algorithms and approaches to match a query text against a set of indexed documents. |
| Starting Page | 28 |
| Ending Page | 30 |
| Page Count | 3 |
| File Format | PDF HTM / HTML |
| DOI | 10.5120/ijca2017913699 |
| Volume Number | 164 |
| Alternate Webpage(s) | https://www.ijcaonline.org/archives/volume164/number6/27489-27489-2017913699?format=pdf |
| Alternate Webpage(s) | https://doi.org/10.5120/ijca2017913699 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
