scholarly journals SEARCH FOR ENTITIES BASED ON THE IMPLICIT SEMANTIC RELATIONS

2019 ◽  
Vol 35 (3) ◽  
pp. 251-266
Author(s):  
Tran Lam Quan ◽  
Vu Tat Thang
Keyword(s):  
Semantic Relations ◽  
Search Model ◽  
Entity Search

The ability to infer undefined information/knowledge by similar inference is one of the natural abilities of human. The paper aims to study, simulate the above ability. The IRS model searches for undefined information/knowledge from an unfamiliar domain using similarities from familiar domains, through query. Because the semantic relations or similarities are not explicitly stated in the query, the IRS model is called an implicit semantic entity search model. The paper presents extracting, clustering, ranking techniques and a model of implicit relational search on Vietnamese language domain.

scholarly journals SEARCH FOR ENTITIES BASED ON THE IMPLICIT SEMANTIC RELATIONS

2019 ◽  
Vol 35 (3) ◽  
pp. 251-266
Author(s):  
Tran Lam Quan ◽  
Vu Tat Thang
Keyword(s):  
Semantic Relations ◽  
Search Model ◽  
Entity Search

The ability to infer undefined information/knowledge by similar inference is one of the natural abilities of human. The paper aims to study, simulate the above ability. The IRS model searches for undefined information/knowledge from an unfamiliar domain using similarities from familiar domains, through query. Because the semantic relations or similarities are not explicitly stated in the query, the IRS model is called an implicit semantic entity search model. The paper presents extracting, clustering, ranking techniques and a model of implicit relational search on Vietnamese language domain.

Fast Neural Network Engine for Natural Science Language Processing: A Drug-Search Case.

2020 ◽  
Author(s):  
Vadim V. Korolev ◽  
Artem Mitrofanov ◽  
Kirill Karpov ◽  
Valery Tkachenko
Keyword(s):  
Neural Network ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Natural Science ◽  
Therapeutic Agent ◽  
Semantic Relations ◽  
Chemical Data ◽  
Processing Methods ◽  
Modern Natural

The main advantage of modern natural language processing methods is a possibility to turn an amorphous human-readable task into a strict mathematic form. That allows to extract chemical data and insights from articles and to find new semantic relations. We propose a universal engine for processing chemical and biological texts. We successfully tested it on various use-cases and applied to a case of searching a therapeutic agent for a COVID-19 disease by analyzing PubMed archive.

THE METADIALOGUE CONCEPT IN ITS LINGUISTIC ASPECT

2019 ◽  
Vol 29 (5) ◽  
pp. 721-726
Author(s):  
Yu.V. Kupriyanova ◽  
I.M. Vasilyanova
Keyword(s):  
Subject Matter ◽  
Dynamic Structure ◽  
Point Of View ◽  
Semantic Relations ◽  
Human Cognition ◽  
Main Research ◽  
Key Points ◽  
Research Findings ◽  
The Subject ◽  
Linguistic Aspect

The article summarizes the key points in the development of the metadialogue phenomenon from a linguistic point of view. Some stages of the development of this concept and the difficulties associated with its structuring are covered. The main research findings of modern foreign and domestic experts on its study are considered. Some characteristics of the subject of the research from the standpoint of various pragmatic installations are given. On the basis of the dynamic structure of the metadialogue development, certain principles of semantic relations connected with the dialectical nature of human cognition are presented. Excursion into the history and evolution of the concept is presented. Several types of formulation of the subject matter are given. In accordance with the goal of speech exposure, internal problems of the development of metadialogue are highlighted and the critical points related to solving these problems are described. The rules of metadialogue flow are explained at the level of steps, the success/failure of which directly affects the final result of communication. The prospects of development of the concept research in accordance with various types of discourse are indicated.

A Lexical Search Model based on word association norms

2019 ◽  
Vol 36 (5) ◽  
pp. 4587-4597
Author(s):  
Jorge Reyes-Magaña ◽  
Gemma Bel-Enguix ◽  
Helena Gómez-Adorno ◽  
Gerardo Sierra
Keyword(s):  
Word Association ◽  
Search Model ◽  
Model Based

scholarly journals Segmented Housing Search

2020 ◽  
Vol 110 (3) ◽  
pp. 720-759 ◽  
Author(s):  
Monika Piazzesi ◽  
Martin Schneider ◽  
Johannes Stroebel
Keyword(s):  
San Francisco ◽  
San Francisco Bay Area ◽  
Supply And Demand ◽  
Housing Markets ◽  
Search Model ◽  
Local Market ◽  
Search Activity ◽  
Bay Area ◽  
Supply And Demand Shocks ◽  
Housing Search

We study housing markets with multiple segments searched by heterogeneous clienteles. In the San Francisco Bay Area, search activity and inventory covary negatively across cities, but positively across market segments within cities. A quantitative search model shows how the endogenous flow of broad searchers to high-inventory segments within their search ranges induces a positive relationship between inventory and search activity across segments with a large common clientele. The prevalence of broad searchers shapes the response of housing markets to localized supply and demand shocks. Broad searchers help spread shocks across many segments and reduce their effect on local market activity. (JEL D83, R21, R31)

Semantic composition of AT-LOCATION relation with other relations

2011 ◽  
Vol 18 (3) ◽  
pp. 343-374
Author(s):  
HAKKI C. CANKAYA ◽  
EDUARDO BLANCO ◽  
DAN MOLDOVAN
Keyword(s):  
Experimental Study ◽  
High Accuracy ◽  
Semantic Relations ◽  
Semantic Composition

AbstractThis paper presents a method for the composition of at-location with other semantic relations. The method is based on inference axioms that combine two semantic relations yielding another relation that otherwise is not expressed. An experimental study conducted on PropBank, WordNet, and eXtended WordNet shows that inferences have high accuracy. The method is applicable to combining other semantic relations and it is beneficial to many semantically intense applications.

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