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http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7827
Title: | Semantic Search and Question-Answering Systems |
Authors: | Pant, Aniruddha PARMAR, PURVA Dept. of Data Science 20181081 |
Keywords: | Natural Language Processing Search Systems Information Retrieval Question-Answering |
Issue Date: | May-2023 |
Citation: | 55 |
Abstract: | Keyword Search Systems have been in wide use since the availability of computers themselves. Keyword search returns the relevant results which contain the exact keywords used in a search query. But in today’s world of extensive information, a simple keyword search is bound to miss a lot of other relevant results which are phrased or written differently. This leads us to develop Semantic Search systems, which can also consider the context and meaning behind a search query, and return results which may not have the exact keywords, but still are relevant because of the intended meaning. This can be taken one-step further by introducing (Extractive) Question-Answering Systems, which if given a question-like query, can directly extract the short answer from the massive wealth of existing information. We explore the development and implementation of such a Semantic Search and Question-Answering system in the domain of finance for a financial product, AlgoFabric, at AlgoAnalytics Pvt. Ltd. |
URI: | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7827 |
Appears in Collections: | MS THESES |
Files in This Item:
File | Description | Size | Format | |
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20181081_Purva_Parmar_MS_Thesis.pdf | MS Thesis | 892.15 kB | Adobe PDF | View/Open |
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