scholarly journals Relation Extraction for Open and Closed Domain Question Answering

2011 ◽  
pp. 171-197 ◽  
Author(s):  
Gosse Bouma ◽  
Ismail Fahmi ◽  
Jori Mur
Keyword(s):  
Question Answering ◽  
Relation Extraction ◽  
Closed Domain

scholarly journals Question Expansion in a Question-Answering System in a Closed-Domain System

2021 ◽  
Vol 183 (23) ◽  
pp. 1-5
Author(s):  
Haniel G. Cavalcante ◽  
Jéferson N. Soares ◽  
José E.B. Maia
Keyword(s):  
Question Answering ◽  
Closed Domain ◽  
Question Answering System

A study on different closed domain question answering approaches

2020 ◽  
Vol 23 (2) ◽  
pp. 315-325
Author(s):  
Srinivasu Badugu ◽  
R. Manivannan
Keyword(s):  
Question Answering ◽  
Closed Domain

scholarly journals Towards relation extraction from Arabic text: a review

2019 ◽  
Vol 5 (5) ◽  
pp. 212-215
Author(s):  
Abeer AlArfaj
Keyword(s):  
Language Processing ◽  
Question Answering ◽  
State Of The Art ◽  
Relation Extraction ◽  
Arabic Language ◽  
Extraction Methods ◽  
The State ◽  
Semantic Relations ◽  
Arabic Text ◽  
Taxonomic Relation

Semantic relation extraction is an important component of ontologies that can support many applications e.g. text mining, question answering, and information extraction. However, extracting semantic relations between concepts is not trivial and one of the main challenges in Natural Language Processing (NLP) Field. The Arabic language has complex morphological, grammatical, and semantic aspects since it is a highly inflectional and derivational language, which makes task even more challenging. In this paper, we present a review of the state of the art for relation extraction from texts, addressing the progress and difficulties in this field. We discuss several aspects related to this task, considering the taxonomic and non-taxonomic relation extraction methods. Majority of relation extraction approaches implement a combination of statistical and linguistic techniques to extract semantic relations from text. We also give special attention to the state of the work on relation extraction from Arabic texts, which need further progress.

scholarly journals Building Graph for Events and Time in Natural Language Text

2020 ◽  
Vol 9 (3) ◽  
pp. 581-586
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Information Extraction ◽  
Language Processing ◽  
Question Answering ◽  
Relation Extraction ◽  
Event Extraction ◽  
Event Time ◽  
Time Graph ◽  
Question Answering Systems

Events and time are two major key terms in natural language processing due to the various event-oriented tasks these are become an essential terms in information extraction. In natural language processing and information extraction or retrieval event and time leads to several applications like text summaries, documents summaries, and question answering systems. In this paper, we present events-time graph as a new way of construction for event-time based information from text. In this event-time graph nodes are events, whereas edges represent the temporal and co-reference relations between events. In many of the previous researches of natural language processing mainly individually focused on extraction tasks and in domain-specific way but in this work we present extraction and representation of the relationship between events- time by representing with event time graph construction. Our overall system construction is in three-step process that performs event extraction, time extraction, and representing relation extraction. Each step is at a performance level comparable with the state of the art. We present Event extraction on MUC data corpus annotated with events mentions on which we train and evaluate our model. Next, we present time extraction the model of times tested for several news articles from Wikipedia corpus. Next is to represent event time relation by representation by next constructing event time graphs. Finally, we evaluate the overall quality of event graphs with the evaluation metrics and conclude the observations of the entire work

scholarly journals Question Analysis for a Closed Domain Question Answering System

2015 ◽  
pp. 468-482 ◽  
Author(s):  
Caner Derici ◽  
Kerem Çelik ◽  
Ekrem Kutbay ◽  
Yiğit Aydın ◽  
Tunga Güngör ◽  
...  
Keyword(s):  
Question Answering ◽  
Closed Domain ◽  
Question Answering System ◽  
Question Analysis
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