scholarly journals Getting answers to natural language questions on the Web

2002 ◽  
Vol 53 (5) ◽  
pp. 359-364 ◽  
Author(s):  
Dragomir R. Radev ◽  
Kelsey Libner ◽  
Weiguo Fan
Keyword(s):  
Natural Language ◽  
The Web

Using NLP for Fact Checking: A Survey

Designs ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 42
Author(s):  
Eric Lazarski ◽  
Mahmood Al-Khassaweneh ◽  
Cynthia Howard
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Computer Science ◽  
Language Processing ◽  
The Internet ◽  
Fake News ◽  
Fact Checking ◽  
The Many ◽  
Human Powered ◽  
The Web

In recent years, disinformation and “fake news” have been spreading throughout the internet at rates never seen before. This has created the need for fact-checking organizations, groups that seek out claims and comment on their veracity, to spawn worldwide to stem the tide of misinformation. However, even with the many human-powered fact-checking organizations that are currently in operation, disinformation continues to run rampant throughout the Web, and the existing organizations are unable to keep up. This paper discusses in detail recent advances in computer science to use natural language processing to automate fact checking. It follows the entire process of automated fact checking using natural language processing, from detecting claims to fact checking to outputting results. In summary, automated fact checking works well in some cases, though generalized fact checking still needs improvement prior to widespread use.

InferPortOIE: A Portuguese Open Information Extraction system with inferences

2018 ◽  
Vol 25 (2) ◽  
pp. 287-306 ◽  
Author(s):  
Cleiton Fernando Lima Sena ◽  
Daniela Barreiro Claro
Keyword(s):  
Natural Language ◽  
Information Extraction ◽  
Digital Data ◽  
Extraction System ◽  
Open Information Extraction ◽  
The Web ◽  
Information Extraction System

AbstractNowadays, there is an increasing amount of digital data. In the case of the Web, daily, a vast collection of data is generated, whose contents are heterogeneous. A significant portion of this data is available in a natural language format. Open Information Extraction (Open IE) enables the extraction of facts from large quantities of texts written in natural language. In this work, we propose an Open IE method to extract facts from texts written in Portuguese. We developed two new rules that generalize the inference by transitivity and by symmetry. Consequently, this approach increases the number of implicit facts in a sentence. Our novel symmetric inference approach is based on a list of symmetric features. Our results confirmed that our method outstands close works both in precision and number of valid extractions. Considering the number of minimal facts, our approach is equivalent to the most relevant methods in the literature.

scholarly journals Identification of Pleonastic It Using the Web

2009 ◽  
Vol 34 ◽  
pp. 339-389 ◽  
Author(s):  
Y. Li ◽  
P. Musilek ◽  
M. Reformat ◽  
L. Wyard-Scott
Keyword(s):  
Natural Language ◽  
Simple Set ◽  
Novel Approach ◽  
The Web

In a significant minority of cases, certain pronouns, especially the pronoun it, can be used without referring to any specific entity. This phenomenon of pleonastic pronoun usage poses serious problems for systems aiming at even a shallow understanding of natural language texts. In this paper, a novel approach is proposed to identify such uses of it: the extrapositional cases are identified using a series of queries against the web, and the cleft cases are identified using a simple set of syntactic rules. The system is evaluated with four sets of news articles containing 679 extrapositional cases as well as 78 cleft constructs. The identification results are comparable to those obtained by human efforts.

scholarly journals Use of ontologies for personalized search of knowledge for natural language texts

2016 ◽  
pp. 073-088
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Information Retrieval ◽  
Natural Language ◽  
Information Resources ◽  
Semantic Search ◽  
Software Implementation ◽  
Open Environment ◽  
Use Of Knowledge ◽  
The Web ◽  
Information Objects ◽  
Search Domain

The paper analyzes the problems of search personalization of information resources and information objects which is based on the construction and use of user task thesaurus. This thesaurus allows the use of knowledge about search domain and structure of information objects represented by some appropriate ontologies. The definitions of semantic search, its subjects and components allow more articulate issues related to the information retrieval in the Web open environment. Software implementation of the proposed approach confirms the effectiveness of its prac-tical use.

scholarly journals Natural Language to SQL query Generation

2021 ◽  
Vol 9 (VI) ◽  
pp. 5069-5072
Author(s):  
Kiran Raj R
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Regular Expression ◽  
Parts Of Speech ◽  
Query Generation ◽  
Sql Query ◽  
Speech Tagging ◽  
The Web

Today, everyone has a personal device to access the web. Every user tries to access the knowledge that they require through internet. Most of the knowledge is within the sort of a database. A user with limited knowledge of database will have difficulty in accessing the data in the database. Hence, there’s a requirement for a system that permits the users to access the knowledge within the database. The proposed method is to develop a system where the input be a natural language and receive an SQL query which is used to access the database and retrieve the information with ease. Tokenization, parts-of-speech tagging, lemmatization, parsing and mapping are the steps involved in the process. The project proposed would give a view of using of Natural Language Processing (NLP) and mapping the query in accordance with regular expression in English language to SQL.

scholarly journals Using of Natural Language Processing Techniques in Suicide Research

2017 ◽  
Vol 1 (2) ◽  
pp. 89 ◽  
Author(s):  
Azam Orooji ◽  
Mostafa Langarizadeh
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Medical Information ◽  
Inclusion Criteria ◽  
Data Set ◽  
Completed Suicide ◽  
Teenagers And Young Adults ◽  
Processing Techniques ◽  
The Web

It is estimated that each year many people, most of whom are teenagers and young adults die by suicide worldwide. Suicide receives special attention with many countries developing national strategies for prevention. Since, more medical information is available in text, Preventing the growing trend of suicide in communities requires analyzing various textual resources, such as patient records, information on the web or questionnaires. For this purpose, this study systematically reviews recent studies related to the use of natural language processing techniques in the area of people’s health who have completed suicide or are at risk. After electronically searching for the PubMed and ScienceDirect databases and studying articles by two reviewers, 21 articles matched the inclusion criteria. This study revealed that, if a suitable data set is available, natural language processing techniques are well suited for various types of suicide related research.

Related Blogs’ Summarization With Natural Language Processing

2020 ◽  
Author(s):  
Niyati Baliyan ◽  
Aarti Sharma
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
The Web ◽  
Content Generation

Abstract There is plethora of information present on the web, on a given topic, in different forms i.e. blogs, articles, websites, etc. However, not all of the information is useful. Perusing and going through all of the information to get the understanding of the topic is a very tiresome and time-consuming task. Most of the time we end up investing in reading content that we later understand was not of importance to us. Due to the lack of capacity of the human to grasp vast quantities of information, relevant and crisp summaries are always desirable. Therefore, in this paper, we focus on generating a new blog entry containing the summary of multiple blogs on the same topic. Different approaches of clustering, modelling, content generation and summarization are applied to reach the intended goal. This system also eliminates the repetitive content giving savings on time and quantity, thereby making learning more comfortable and effective. Overall, a significant reduction in the number of words in the new blog generated by the system is observed by using the proposed novel methodology.

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