| Título |
Information Retrieval-Based Question Answering System on Foods and Recipes |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
19th Mexican International Conference on Artificial Intelligence, MICAI 2020 |
| Resumen |
Question Answering (QA) is an emerging domain of research that retrieves a textual segment from the set of documents in response to user’s queries. To recommend the answer in response to cooking recipe related questions is just an early stage of research and requires the significant refinement. In this paper, we have developed a question answering system on cooking recipes by using Natural Language Processing (NLP) and Information Retrieval (IR) technique. In recent years, with the rapid growth of information, the IR system has more importance in question answering domain. Users can also face difficulties to find expected answers from a huge amount of information. QA solves the information-overloading problem and IR returns the precise answers to the users. Answers from search engines are not only the results for a user’s query but these collective words should justify the questions. We have a standard dataset on recipes and foods from famous cities in India which is collected from various Indian recipe websites. We have used Apache Lucene for information retrieval and we have prepared the gold standard dataset for the question answering system on cooking recipes. © 2020, Springer Nature Switzerland AG. |
| Observaciones |
DOI 10.1007/978-3-030-60887-3_23
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), V. 12469 |
| Lugar |
Ciudad de México |
| País |
Mexico |
| No. de páginas |
260-270 |
| Vol. / Cap. |
12469 LNAI |
| Inicio |
2020-10-12 |
| Fin |
2020-10-17 |
| ISBN/ISSN |
9783030608866 |
