scholarly journals Towards a Recommendation System for the Learner from a Semantic Model of Knowledge in a Collaborative Environment

2015 ◽  
pp. 315-327 ◽  
Author(s):  
Chahrazed Mediani ◽  
Marie-Hélène Abel ◽  
Mahieddine Djoudi
Keyword(s):  
Recommendation System ◽  
Semantic Model ◽  
Collaborative Environment

Analysis on Research Paper Publication Recommendation System with Composition of Papers and Conferences Matrices

2020 ◽  
pp. 120-127
Author(s):  
Htay Htay Win ◽  
Aye Thida Myint ◽  
Mi Cho Cho
Keyword(s):  
Social Network ◽  
Dimensionality Reduction ◽  
Correspondence Analysis ◽  
Recommendation System ◽  
Research Paper ◽  
Topic Modelling ◽  
Research Papers ◽  
The Right ◽  
Publication Recommendation

For years, achievements and discoveries made by researcher are made aware through research papers published in appropriate journals or conferences. Many a time, established s researcher and mainly new user are caught up in the predicament of choosing an appropriate conference to get their work all the time. Every scienti?c conference and journal is inclined towards a particular ?eld of research and there is a extensive group of them for any particular ?eld. Choosing an appropriate venue is needed as it helps in reaching out to the right listener and also to further one’s chance of getting their paper published. In this work, we address the problem of recommending appropriate conferences to the authors to increase their chances of receipt. We present three di?erent approaches for the same involving the use of social network of the authors and the content of the paper in the settings of dimensionality reduction and topic modelling. In all these approaches, we apply Correspondence Analysis (CA) to obtain appropriate relationships between the entities in question, such as conferences and papers. Our models show hopeful results when compared with existing methods such as content-based ?ltering, collaborative ?ltering and hybrid ?ltering.

Towards Small-Sized Long Tail Business with the Dual-Directed Recommendation System

2010 ◽  
Vol 130 (2) ◽  
pp. 317-323
Author(s):  
Masakazu Takahashi ◽  
Takashi Yamada ◽  
Kazuhiko Tsuda ◽  
Takao Terano
Keyword(s):  
Recommendation System ◽  
Long Tail

A Prototype for Software Refactoring Recommendation System

2020 ◽  
Vol 16 (7) ◽  
pp. 1095
Author(s):  
Gao Yuan ◽  
Zhang Youchun ◽  
Lu Wenpen ◽  
Luo Jie ◽  
Hao Daqing
Keyword(s):  
Recommendation System ◽  
Software Refactoring

Modelling of Semantic Processes and Evolutional Semantic Model

2019 ◽  
Vol 26 (27) ◽  
pp. 197-210 ◽  
Author(s):  
Anastasia Fedorova
Keyword(s):  
Key Words ◽  
Dynamic Models ◽  
Scientific Literature ◽  
Semantic Model ◽  
Vast Array ◽  
Special Procedure ◽  
Semantic Models ◽  
Semantic Evolution ◽  
Semantic Processes ◽  
The Way

In Linguistics the terms model and modelling have a vast array of meanings, which depends on the purpose and the object, and the type of the scientific research. The article is dedicated to the investigation of a special procedure of semantic processes modelling, deducing and substantiating the notion “evolutional semantic model”, the content and operational opportunities of which differ drastically from the essence and purpose of the known from the scientific literature phenomenon of the same name. In the proposed research this variety of modelling is oriented towards the description of the dynamics of the legal terms content loading, the estimation of possible vectors of the semantic evolution on the way of its terminalization/determinalization. The evolutional model of semantics has here as its basis the succession of sememes or series of sememes, the order of which is determined with accounting of a number of parameters. The typical schemes of the meaning development, illustrated by the succession of sememes, are considered to be the models of semantic laws (evolutional semantic models = EMS). Their function is the explanation of the mechanism and the order of the stages of the semantic evolution of the system of the words which sprung from one root on the way of its legal specialization, and, therefore, the proposed in the paper experience of semantic laws modelling differs from the expertise of the “catalogue of semantic derivations”, proposed by H. A. Zaliznjak, which doesn’t have as its purpose the explanation of meaning displacements, and from the notion of semantic derivation, models of derivation, dynamic models, worked out by O. V. Paducheva, which also only state such a displacement, without proving its reality. Key words: evolutional semantic model (EMS), modelling, semantic law, sememe, pre(law).

A Recommender System for Inverse Design of Polycarbonates and Polyesters

2020 ◽  
Author(s):  
Nathaniel Park ◽  
Dmitry Yu. Zubarev ◽  
James L. Hedrick ◽  
Vivien Kiyek ◽  
Christiaan Corbet ◽  
...  
Keyword(s):  
Ring Opening ◽  
High Performance ◽  
Recommendation System ◽  
Polymeric Materials ◽  
Monomer Conversion ◽  
Design Strategy ◽  
Ring Opening Polymerization ◽  
Inverse Design ◽  
False Negatives ◽  
Accelerate Development

The convergence of artificial intelligence and machine learning with material science holds significant promise to rapidly accelerate development timelines of new high-performance polymeric materials. Within this context, we report an inverse design strategy for polycarbonate and polyester discovery based on a recommendation system that proposes polymerization experiments that are likely to produce materials with targeted properties. Following recommendations of the system driven by the historical ring-opening polymerization results, we carried out experiments targeting specific ranges of monomer conversion and dispersity of the polymers obtained from cyclic lactones and carbonates. The results of the experiments were in close agreement with the recommendation targets with few false negatives or positives obtained for each class.<br>

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