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Answering comparison in indonesian question answering system with database
Saelan A.a, Purwarianti A.a, Widyantoro D.H.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018, School of Electrical Engineering and Informatics. All rights reserved.In this research, we build a question answering system that can answer comparative questions. Our system contains two components, question analysis and answer processing. In question analysis, we use information extraction method to extract entities, aspects, relations, and constants from the question. We also classify the question into five question types such as entity-mentioned, entity-other, entity-all, aspect, and yes/no. These processes in question analysis component are solved by machine learning technique. In answer processing component, we process the comparison by using word lists and rules. The result of comparison processing is used to find the answer by generating query to get relevant data from the database. The query generation process is performed by using rules based on the question type. After that, the data from database is also processed based on question type to generate the answer. Based on the experiment results, our proposed method for comparison question answering system is promising.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Comparative question,Comparison,Database,Information extraction,Question answering[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]This research is partially supported by “Penelitian Pendidikan Magister menuju Doktor untuk Sarjana Unggul” (Master’s Program toward Doctoral Degree for Excellent Graduate) from Kemenristekdikti (Indonesian ministry of research, technology, and higher education) within research “Pengembangan Chatbot Berbahasa Indonesia” (Indonesian Chatbot Development).[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.15676/ijeei.2018.10.4.11[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]