scholarly journals A Rating-Based Integrated Recommendation Framework with Improved Collaborative Filtering Approaches

2017 ◽  
Vol 12 (3) ◽  
pp. 307
Author(s):  
Shulin Cheng ◽  
Bofeng Zhang ◽  
Guobing Zou
Keyword(s):  
Collaborative Filtering ◽  
Prediction Accuracy ◽  
Information Sources ◽  
Information Source ◽  
Strong Robustness ◽  
Personal Recommendation ◽  
Rating Prediction ◽  
Interest Model ◽  
Low Sensitivity ◽  
Individual Information

Collaborative filtering (CF) approach is successfully applied in the rating prediction of personal recommendation. But individual information source is leveraged in many of them, i.e., the information derived from single perspective is used in the user-item matrix for recommendation, such as user-based CF method mainly utilizing the information of user view, item-based CF method mainly exploiting the information of item view. In this paper, in order to take full advantage of multiple information sources embedded in user-item rating matrix, we proposed a rating-based integrated recommendation framework of CF approaches to improve the rating prediction accuracy. Firstly, as for the sparsity of the conventional item-based CF method, we improved it by fusing the inner similarity and outer similarity based on the local sparsity factor. Meanwhile, we also proposed the improved user-based CF method in line with the user-item-interest model (UIIM) by preliminary rating. Second, we put forward a background method called user-item-based improved CF (UIBCF-I), which utilizes the information source of both similar items and similar users, to smooth itembased and user-based CF methods. Lastly, we leveraged the three information sources and fused their corresponding ratings into an Integrated CF model (INTE-CF). Experiments demonstrate that the proposed rating-based INTE-CF indeed improves the prediction accuracy and has strong robustness and low sensitivity to sparsity of dataset by comparisons to other mainstream CF approaches.

scholarly journals An Adaptive Social Network-Aware Collaborative Filtering Algorithm for Improved Rating Prediction Accuracy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 68301-68310 ◽  
Author(s):  
Dionisis Margaris ◽  
Anna Kobusinska ◽  
Dimitris Spiliotopoulos ◽  
Costas Vassilakis
Keyword(s):  
Social Network ◽  
Collaborative Filtering ◽  
Prediction Accuracy ◽  
Filtering Algorithm ◽  
Collaborative Filtering Algorithm ◽  
Rating Prediction

A Collaborative Filtering Recommendation Algorithm Based on Cloud Model, Item Attribute and User Data

2014 ◽  
Vol 610 ◽  
pp. 747-751
Author(s):  
Jian Sun ◽  
Xiao Ying Chen
Keyword(s):  
Collaborative Filtering ◽  
Prediction Accuracy ◽  
Cloud Model ◽  
Prediction Algorithm ◽  
Recommendation Algorithm ◽  
Rating Data ◽  
User Data ◽  
Item Attribute ◽  
Rating Prediction ◽  
User Ratings

Aiming at the problems of extremely sparse of user-item rating data and poor recommendation quality, we put forward a collaborative filtering recommendation algorithm based on cloud model, item attribute and user data which combined with the existing literatures. A rating prediction algorithm based on cloud model and item attribute is proposed, based on idea that the similar users rating for the same item are similar and the same user ratings for the similar items are similar and stable. Through compare and analysis this paper’s and other studies experimental results, we get the conclusion that the rating prediction accuracy is improved.

scholarly journals Augmenting Black Sheep Neighbour Importance for Enhancing Rating Prediction Accuracy in Collaborative Filtering

2021 ◽  
Vol 11 (18) ◽  
pp. 8369
Author(s):  
Dionisis Margaris ◽  
Dimitris Spiliotopoulos ◽  
Costas Vassilakis
Keyword(s):  
Collaborative Filtering ◽  
Prediction Error ◽  
Prediction Accuracy ◽  
Supplementary Information ◽  
Similarity Metrics ◽  
Sources Of Information ◽  
Black Sheep ◽  
Error Metrics ◽  
Target User ◽  
Rating Prediction

In this work, an algorithm for enhancing the rating prediction accuracy in collaborative filtering, which does not need any supplementary information, utilising only the users’ ratings on items, is presented. This accuracy enhancement is achieved by augmenting the importance of the opinions of ‘black sheep near neighbours’, which are pairs of near neighbours with opinion agreement on items that deviates from the dominant community opinion on the same item. The presented work substantiates that the weights of near neighbours can be adjusted, based on the degree to which the target user and the near neighbour deviate from the dominant ratings for each item. This concept can be utilized in various other CF algorithms. The experimental evaluation was conducted on six datasets broadly used in CF research, using two user similarity metrics and two rating prediction error metrics. The results show that the proposed technique increases rating prediction accuracy both when used independently and when combined with other CF algorithms. The proposed algorithm is designed to work without the requirements to utilise any supplementary sources of information, such as user relations in social networks and detailed item descriptions. The aforesaid point out both the efficacy and the applicability of the proposed work.

scholarly journals Doctors as disseminators? Practicing physicians as multipliers for community-based prevention networks in a large city in western Germany

2021 ◽  
Author(s):  
Katharina Kreffter ◽  
Simon Götz ◽  
Stefanie Lisak-Wahl ◽  
Thuy Ha Nguyen ◽  
Nico Dragano ◽  
...  
Keyword(s):  
Parental Education ◽  
Information Sources ◽  
Information Source ◽  
Entrance Examination ◽  
Parenting Skills ◽  
Language Therapy ◽  
Community Based ◽  
Social Differences ◽  
Immigrant Background ◽  
Practicing Physicians

Abstract Aim Practicing physicians have a special position as disseminators of community-based prevention for children. However, it is unclear to what extent physicians inform parents about programs. The study investigated: To what extent do physicians disseminate information about community-based prevention for children aged 0–7? Do differences exist along family’s socioeconomic position (SEP) and immigrant background? Subject and methods We conducted a retrospective cohort study in a German school entrance examination. Parents were invited to participate in a survey on community-based prevention with information about their awareness and information source. SEP was measured by parental education, immigrant background by country of birth. For nine services types, we counted how often parents named physicians and other professional groups as information sources. To estimate social differences, we calculated adjusted odds ratios (OR) with 95% confidence interval (CI). Results Survey participants included 6480 parents (response 65.49%). Compared to other information sources, physicians were mentioned less frequently. For example, regarding language therapy, 31.2% of parents were informed by healthcare/social services, and 4.4% by physicians. Lower educated parents were less frequently informed by physicians about counseling services (OR 0.58; 95% CI 0.46–0.73) compared to higher educated parents. Parents with immigrant background were informed less often about parenting skills courses (OR 0.79; 95% CI 0.70–0.90) compared to parents without immigrant background, but more often about language therapy (OR 1.47; 95% CI 1.13–1.91). No further social differences were observed. Conclusion The role of physicians as disseminators for community-based prevention is expandable. They should promote parenting skills courses in a socially sensitive way.

scholarly journals A Collaborative Filtering Algorithm with Intragroup Divergence for POI Group Recommendation

2021 ◽  
Vol 11 (12) ◽  
pp. 5416
Author(s):  
Yanheng Liu ◽  
Minghao Yin ◽  
Xu Zhou
Keyword(s):  
Collaborative Filtering ◽  
User Preference ◽  
Computation Method ◽  
Group Recommendation ◽  
Preference Rating ◽  
Filtering Method ◽  
Personal Recommendation ◽  
Collaborative Filtering Algorithm ◽  
Group Members ◽  
Individual Recommendation

The purpose of POI group recommendation is to generate a recommendation list of locations for a group of users. Most of the current studies first conduct personal recommendation and then use recommendation strategies to integrate individual recommendation results. Few studies consider the divergence of groups. To improve the precision of recommendations, we propose a POI group recommendation method based on collaborative filtering with intragroup divergence in this paper. Firstly, user preference vector is constructed based on the preference of the user on time and category. Furthermore, a computation method similar to TF-IDF is presented to compute the degree of preference of the user to the category. Secondly, we establish a group feature preference model, and the similarity of the group and other users’ feature preference is obtained based on the check-ins. Thirdly, the intragroup divergence of POIs is measured according to the POI preference of group members and their friends. Finally, the preference rating of the group for each location is calculated based on a collaborative filtering method and intragroup divergence computation, and the top-ranked score of locations are the recommendation results for the group. Experiments have been conducted on two LBSN datasets, and the experimental results on precision and recall show that the performance of the proposed method is superior to other methods.

scholarly journals “I actually got my first job through my ex-colleague”: Employment-related information seeking behavior of Bangladeshi immigrants in Canada

2021 ◽  
pp. 096100062199280
Author(s):  
Nafiz Zaman Shuva
Keyword(s):  
Information Seeking ◽  
Information Needs ◽  
Information Sources ◽  
Information Source ◽  
Occupational Status ◽  
Structured Interviews ◽  
Related Information ◽  
Immigrant Professionals ◽  
Government Of Canada ◽  
First Job

This study explores the employment-related information seeking behaviour of Bangladeshi immigrants in Canada. Using a mixed-methods approach, the study conducted semi-structured interviews with 60 Bangladeshi immigrants in Ontario, Canada, and obtained 205 survey responses. The study highlights the centrality of employment-related settlement among Bangladeshi immigrants in Ontario and reports many immigrants not being able to utilize their education and skills after arrival in Canada. The results show that Bangladeshi immigrants utilize various information sources for their employment in Canada, including friends and professional colleagues, online searchers, and settlement agencies. Although Bangladeshi immigrants utilized a large array of information sources for meeting their employment-related information needs, many interview participants emphasized that the employment-related benefits they received was because of their access to friends and professional colleagues in Canada. The survey results echoed the interview findings. The cross-tabulation results on post-arrival information sources and occupation status as well as first job information sources and occupational status in Canada show a significant association among the use of the information source “friends and professional colleagues in Canada” and immigrants’ occupational status. The study highlights the benefits of professional colleagues among immigrants in employment-related settlement contexts. It also reports the challenges faced by many immigrant professionals related to employment-related settlement because of the lack of access to their professional friends and colleagues in Canada. The author urges the Federal Government of Canada, provincial governments, and settlement agencies working with newcomers to offer services that would connect highly skilled immigrants with their professional networks in Canada, in order to get proper guidance related to obtaining a professional job or alternative career. The author calls for further studies on employment-related information seeking by immigrants to better understand the role information plays in their settlement in a new country.

scholarly journals Information Source Quality in Intelligent Transport Systems

2012 ◽  
Vol 22 (2) ◽  
pp. 125-131 ◽  
Author(s):  
Niko Jelušić ◽  
Mario Anžek ◽  
Božidar Ivanković
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Information Sources ◽  
Information Source ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Traffic System ◽  
Intelligent Transport ◽  
Real Time Information ◽  
Time Information

Advanced automatic traffic control systems and various other ITS (Intelligent Transport Systems) applications and services rely on real-time information from the traffic system. This paper presents the overview and general functions of different information sources which provide real-time information that are used or could be used in ITS. The objective is to formally define the quality of information sources suitable for ITS based on formal models of the traffic system and information sources. The definition of quality encompasses these essential factors: traffic system information that exists or may be requested, user requirements and attributes that describe the information sources. This provides the framework and guidelines for the evaluation of information sources that accounts for relevant factors that influence their selection for specific ITS applications. KEY WORDS: information source, information source quality, Intelligent Transport Systems (ITS), automatic traffic control

scholarly journals Immunisation with BCG in the Maringue District, Sofala Province, Mozambique

2013 ◽  
Vol 2013 ◽  
pp. 1-4 ◽  
Author(s):  
Dario Consonni ◽  
Marina Margarida Montenegro Agorostos Karagianis ◽  
Giuseppe Bufardeci
Keyword(s):  
Child Health ◽  
Vaccination Coverage ◽  
Information Sources ◽  
Maternal Child Health ◽  
Health Unit ◽  
Immunisation Coverage ◽  
Bacille Calmette Guerin ◽  
Information Recording ◽  
Home Deliveries ◽  
Individual Information

Objectives. We evaluated immunisation with Bacille Calmette-Guérin (BCG) among newborns in 2011 in the Maringue District, Sofala Province, Mozambique, which includes seven health units. The study was motivated by the fact that in official reports, immunisation coverage was unreliable (more than 100%).Methods. The office of maternal-child health of the central Maringué-Sede health unit provided the number of live newborns in 2011 at the maternal clinics of the seven health units and an estimate of the number of home deliveries. From vaccination registers, we abstracted records of BCG vaccinations administered in the period 01/01/2011–30/06/2012 to children born in 2011.Results. The number of live newborns was 3,353. Overall, the number of BCG vaccinations administered was 2,893, with a coverage of 86.3%.Conclusion. In this study, we could only calculate an approximate coverage estimate, because of unavailability of adequate individual information. Recording practices should be changed in order to allow use of individual information and linkage across different information sources and thus a more precise vaccination coverage assessment.

Sources of Performance Information in the Exercise Setting

1990 ◽  
Vol 12 (1) ◽  
pp. 56-65 ◽  
Author(s):  
Vicki Ebbeck
Keyword(s):  
Goal Setting ◽  
Muscle Development ◽  
Information Sources ◽  
Weight Training ◽  
Function Analysis ◽  
Information Source ◽  
Student Feedback ◽  
Sources Of Information ◽  
Perceived Effort ◽  
Gender Groups

This study examined the sources of information used by adult exercisers to judge performance. Of particular interest was the investigation of gender differences. Subjects, 271 adults (174 males, 97 females) who were enrolled in a university weight training program, completed a questionnaire designed to evaluate the importance of 12 information sources in judging weight training performance: instructor feedback, student feedback, student comparison, changes noticed outside the gym, personal attraction toward the activity, degree of perceived effort exerted in the workout, performance in workout, feedback from others not in the class, goal setting, muscle development, workout improvement over time, and ease in learning new skills. Results revealed a significant discriminant function analysis for gender, with six information sources entering the stepwise procedure: goal setting, student feedback, learning, effort, improvement, and changes noticed outside the gym differentiated the gender groups. Males relied more than females on student feedback as an information source to judge performance. Alternatively, females used effort, goal setting, improvement, and learning as information sources more than males.

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