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.

scholarly journals Analysis on Research Paper Publication Recommender System with Authors - Conferences Matrix

2020 ◽  
pp. 195-202
Author(s):  
Htay Htay Win
Keyword(s):  
Social Network ◽  
Dimensionality Reduction ◽  
Correspondence Analysis ◽  
Recommender System ◽  
Research Paper ◽  
Topic Modelling ◽  
Research Papers ◽  
The Right

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.

scholarly journals A Study on Publication Recommender System with Content Modelling

2020 ◽  
pp. 399-403
Author(s):  
Htay Htay Win
Keyword(s):  
Social Network ◽  
Dimensionality Reduction ◽  
Correspondence Analysis ◽  
Recommender System ◽  
Topic Modelling ◽  
Research Papers ◽  
The Right

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.

scholarly journals Recommendation System

2021 ◽  
Vol 6 (12) ◽  
pp. 484-492
Author(s):  
Dr. ML Sharma C Vinay Kumar Saini and Jai Raj Singh
Keyword(s):  
Recommender System ◽  
Recommendation System ◽  
Research Paper ◽  
Research Field ◽  
Collaborative Approach ◽  
Research Papers ◽  
Area Of Interest ◽  
Overall Performance ◽  
The Right ◽  
Filtering Approach

Research paper recommenders emerged over the last decade to ease finding publications relating to researchers’ area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collab- orative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommen- dations. The novelty of our proposed approach is that it provides personalized recommen- dations regardless of the research field and regardless of the user’s expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list.

scholarly journals Suggesting new words to extract keywords from title and abstract

2019 ◽  
Vol 9 (5) ◽  
pp. 4441 ◽  
Author(s):  
Hadeel Qasem Gheni ◽  
Ahmed Mohammed Hussein ◽  
Wed Kadhim Oleiwi
Keyword(s):  
Research Paper ◽  
Research Papers ◽  
New Words ◽  
Writing Research ◽  
The Many ◽  
The Right

When talking about the fundamentals of writing research papers, we find that keywords are still present in most research papers, but that does not mean that they exist in all of them, we can find papers that do not contain keywords. Keywords are those words or phrases that accurately reflect the content of the research paper. Keywords are an exact abbreviation of what the research carries in its content. The right keywords may increase the chance of finding the article or research paper and chances of reaching more people who should reach them. The importance of keywords and the essence of the research and address is mainly to attract these highly specialized and highly influential writers in their fields and who specialize in reading what holds the appropriate characteristics but they do not read and cannot read everything. In this paper, we extract new keywords by suggesting a set of words, these words were suggested according to the many mentioned in the researches with multiple disciplines in the field of computer. In our system, we take a number of words (as many as specified in the program) that come before the proposed words and consider it as new keywords. This system proved to be effective in finding keywords that correspond to some extent with the keywords developed by the author in his research.

scholarly journals Need of Sentiments Analysis with CF for Quality Recommendations

2021 ◽  
Vol 5 (2) ◽  
pp. 1-5
Author(s):  
Seema P. Nehete ◽  
Satish R. Devane
Keyword(s):  
Neural Network ◽  
Recommendation System ◽  
Research Papers ◽  
High Recall ◽  
User Reviews ◽  
Target User ◽  
Artificial Neural Network Ann ◽  
Quality Of Products ◽  
The Right

Recommendation system (RS) help user for purchasing the right product of their interest within the affordable right price. Presently many RS make use of only filtering methods to recommend products to the user which is not taking care of the quality of products. Quality of products can be found from textual reviews available on various e-commerce websites and hence this RS performs Sentiment Analysis (SA)of extracted relevant textual reviews along with Collaborative Filtering (CF) to give accurate and good quality recommendations to the user. Reviews are analyzed using optimized Artificial Neural Network (ANN) which shows notified improvement than traditional ANN on real-time extracted data of reviews.CF performance is proved by using the standard dataset of movilense used in many research papers. Results show high recall and accuracy of CF for the recommendation of products to the target user.

The Right to Health in Relation to Human Rights

LAW REVIEW ◽  
2018 ◽  
Vol 37 (01) ◽  
Author(s):  
Lily Srivastava
Keyword(s):  
Public Health ◽  
Human Rights ◽  
Research Paper ◽  
Right To Health ◽  
Health Issues ◽  
Research Papers ◽  
Indian Health ◽  
Health Goals ◽  
The Right ◽  
Health Rights

Laws are an essential tool for improving public health capacity and thus for their public health outcomes. Effective responses to emerging threats and the attainment of public health goals require that the International world, States, their governments and partner organizations be legally prepared. Public health law focuses on the nexus between law, public health and the legal tools applicable to public health issues. The second part of the research paper attempts to analysis of the existing National and International guidelines, and Legislations in relation to health policy of India and access the need for a rights sensitive legislation. Third part of the research papers explores the judicial contribution in establishing right to health as basic human rights. Fourth part compares Indian health rights with some other countries. Finally the research paper suggests some recommendations that exists for a contemporary framework with proper implementation to address this issue

scholarly journals A Subspace Clustering Framework for Research Group Collaboration

2011 ◽  
pp. 96-116
Author(s):  
Nitin Agarwal ◽  
Ehtesham Haque ◽  
Huan Liu ◽  
Lance Parsons
Keyword(s):  
Recommender Systems ◽  
Clustering Algorithm ◽  
Recommendation System ◽  
Subspace Clustering ◽  
Research Paper ◽  
High Dimensional ◽  
Research Papers ◽  
The Core ◽  
Benchmark Datasets ◽  
Research Paper Recommender Systems

Researchers spend considerable time searching for relevant papers on the topic in which they are currently interested. Often, despite having similar interests, researchers in the same lab do not find it convenient to share results of bibliographic searches and thus conduct independent time-consuming searches. Research paper recommender systems can help the researcher avoid such time-consuming searches by allowing each researcher to automatically take advantage of previous searches performed by others in the lab. Existing recommender systems were developed for commercial domains to assist users by focusing towards products of their interests. Unlike those domains, the research paper domain has relatively few users when compared with the huge number of research papers. In this paper we present a novel system to recommend relevant research papers to a user based on the user’s recent querying and browsing habits. The core of the system is a scalable subspace clustering algorithm, SCuBA (Subspace ClUstering Based Analysis) that performs well on the sparse, high-dimensional data collected in this domain. Both synthetic and benchmark datasets are used to evaluate the recommendation system and to demonstrate that it performs better than the traditional collaborative filtering approaches when recommending research papers.

Cold Start Problem Alleviation in a Research Paper Recommendation System Using the Random Walk Approach on a Heterogeneous User-Paper Graph

2020 ◽  
Vol 16 (2) ◽  
pp. 24-48
Author(s):  
Manju G. ◽  
Abhinaya P. ◽  
Hemalatha M.R. ◽  
Manju Ganesh G. ◽  
Manju G.G.
Keyword(s):  
Social Network ◽  
Random Walk ◽  
Social Interaction ◽  
Recommendation System ◽  
Cold Start ◽  
Research Paper ◽  
Novel Approach ◽  
Interaction Factor ◽  
The Social ◽  
Cold Starts

Recommendation approaches generally fail to recommend newly-published papers as relevant, owing to the lack of prior information about the said papers and, more particularly, problems associated with cold starts. It would appear, to all intents and purposes, that researchers currently interact more on social networks than they normally would in academic circles, and relationships of a purely academic nature have witnessed a paradigm shift, in keeping with this new trend. In existing paper recommendation methods, the social interaction factor has yet to play a pivotal role. The authors propose a social network-based research paper recommendation method, that alleviates cold start problems by incorporating users' social interaction, as well as topical relevancy, among assorted papers in the Mendeley academic social network using a novel approach, random walk Ergodic Markov Chain. The system yields improved results after cold start alleviation, compared with the existing system.

Analytical Study of Violence Theme in Victoria Schwab’s This Savage Song

2019 ◽  
Keyword(s):  
Analytical Study ◽  
Research Paper ◽  
The Novel ◽  
Vicious Cycle ◽  
Aggressive Approach ◽  
Research Article ◽  
The People ◽  
The Social ◽  
Different Dimensions ◽  
The Right

This research article focuses on the theme of violence and its representation by the characters of the novel “This Savage Song” by Victoria Schwab. How violence is transmitted through genes to next generations and to what extent socio- psycho factors are involved in it, has also been discussed. Similarly, in what manner violent events and deeds by the parents affect the psychology of children and how it inculcates aggressive behaviour in their minds has been studied. What role is played by the parents in grooming the personality of children and ultimately their decisions to choose the right or wrong way has been argued. In the light of the theory of Judith Harris, this research paper highlights all the phenomena involved: How the social hierarchy controls the behaviour. In addition, the aggressive approach of the people in their lives has been analyzed in the light of the study of second theorist Thomas W Blume. As the novel is a unique representation of supernatural characters, the monsters, which are the products of some cruel deeds, this research paper brings out different dimensions of human sufferings with respect to these supernatural beings. Moreover, the researcher also discusses that, in what manner the curse of violence creates an inevitable vicious cycle of cruel monsters that makes the life of the characters turbulent and miserable.

Unsupervised dimensionality reduction for very large datasets: Are we going to the right direction?

2020 ◽  
Vol 196 ◽  
pp. 105777
Author(s):  
Jadson Jose Monteiro Oliveira ◽  
Robson Leonardo Ferreira Cordeiro
Keyword(s):  
Dimensionality Reduction ◽  
Large Datasets ◽  
Very Large Datasets ◽  
The Right
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