A novel recommendation system based on semantics and context awareness

Computing ◽  
2018 ◽  
Vol 100 (8) ◽  
pp. 809-823 ◽  
Author(s):  
Qin Yang
Keyword(s):  
Context Awareness ◽  
Recommendation System

Using RSSI Simple Localization Method to Implement the Context-Aware and Social Recommendation System

2013 ◽  
Vol 479-480 ◽  
pp. 1213-1217
Author(s):  
Mu Yen Chen ◽  
Ming Ni Wu ◽  
Hsien En Lin
Keyword(s):  
Social Media ◽  
Social Relations ◽  
Context Awareness ◽  
Recommendation System ◽  
Product Information ◽  
Indoor Localization ◽  
Context Aware ◽  
Social Recommendation ◽  
Localization Method ◽  
The Social

This study integrates the concept of context-awareness with association algorithms and social media to establish the Context-aware and Social Recommendation System (CASRS). The Simple RSSI Indoor Localization Module (SRILM) locates the user position; integrating SRILM with Apriori Recommendation Module (ARM) provides effective recommended product information. The Social Media Recommendation Module (SMRM) connects to users social relations, so that the effectiveness for users to gain product information is greatly enhanced. This study develops the system based on actual context.

scholarly journals Recommendation System for Sightseeing Tours

2020 ◽  
Vol 4 (2) ◽  
pp. 34-54
Author(s):  
Ricardo Claudino Valadas ◽  
Elizabeth Simão Carvalho
Keyword(s):  
Context Awareness ◽  
Recommendation System ◽  
Response Times ◽  
External Application ◽  
Points Of Interest ◽  
Tourism Sector ◽  
Current Location ◽  
Application Programming ◽  
Programming Interfaces ◽  
Positive Results

This research proposes a model of a recommendation system (RS) for tourist itineraries. The RS suggests tips of what to visit in a city, based on the available time, personal preferences, current geo-location, and the user's context awareness. These suggestions are calculated based on the treatment of collected data in real time by external application programming interfaces, through a list of points of interest located within a radius that can be reached by the user. Preliminary tests validated the model's goals and its potential in the tourism sector. The RS for tourist itineraries proposed is based on four essential points, in order to make the experience different and well as possible: end-user's personal tastes, the time available, end-user's current location, and context awareness. The performance tests that were carried out brought very positive results and showed that the RS presented a number of requisitions proportional to the server response times and algorithm. The functionality tests were quite positive, with percentages of experience of using the RS between 62.5% and 100%.

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
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