Question answering system for railway schedule (Record no. 4931)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01909nam a22001817a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220107122808.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 160301b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Arun As (92213001) |
| 9 (RLIN) | 8284 |
| 245 ## - TITLE STATEMENT | |
| Title | Question answering system for railway schedule |
| 502 ## - DISSERTATION NOTE | |
| Degree type | Master of Science in Computational Science |
| Name of granting institution | 2013-2015 |
| Year degree granted | EXT |
| -- | T.K Manoj Kumar |
| -- | Radhika Mamidi ( Assistant professor) |
| Miscellaneous information | " International Institute of Information Technology-Hyderabad" |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Using a computer to answer questions has been a human dream since the beginning of the digital era. A first step towards the achievement of such an ambitious goal is to deal with natural language to enable the computer to understand what its user asks. The discipline that studies the connection between natural language and the representation of its meaning via computational models is computational linguistics. According to such discipline, Question Answering can be defined as the task that, given a question formulated in natural language, aims at finding one or more concise answers. Here I am implementing question answering system in railway schedule. The system will handle seven types of queries. The domain will be the local train schedule in Trivandrum central railway station. This is a template based system. If we are giving a natural language question, the question run on the Stanford parser and extracting the key word from the parser and fill it in the template. Here the templates are from station, to station, via station, train name, train number, arrival time, departure time etc. If any template is missing it will form a query and run on the database and give the answer from database. The final output we get is in natural language. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | INFORMATION SYSTEMS |
| 9 (RLIN) | 8285 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | INFORMATION RETRIEVAL |
| 9 (RLIN) | 8286 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | NATURAL LANGUAGE PROCESSING |
| 9 (RLIN) | 8287 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | IIITM-K | Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre | 01/03/2016 | R-648 | 01/03/2016 | 01/03/2016 | Project Reports |