scholarly journals A Data-Driven Personalized Lighting Recommender System

2021 ◽  
Vol 4 ◽  
Author(s):  
Atousa Zarindast ◽  
Jonathan Wood
Keyword(s):  
Recommender System ◽  
Geographical Location ◽  
User Preferences ◽  
Geographical Information ◽  
User Interest ◽  
Smart Lighting ◽  
Home Based ◽  
Product Service ◽  
Color Scheme ◽  
Do So

Recommender systems attempt to identify and recommend the most preferable item (product-service) to individual users. These systems predict user interest in items based on related items, users, and the interactions between items and users. We aim to build an auto-routine and color scheme recommender system for home-based smart lighting that leverages a wealth of historical data and machine learning methods. We utilize an unsupervised method to recommend a routine for smart lighting. Moreover, by analyzing users’ daily logs, geographical location, temporal and usage information, we understand user preferences and predict their preferred light colors. To do so, users are clustered based on their geographical information and usage distribution. We then build and train a predictive model within each cluster and aggregate the results. Results indicate that models based on similar users increases the prediction accuracy, with and without prior knowledge about user preferences.

A Dynamic Recommender System with Fused Time and Location Factors

2019 ◽  
Vol 23 (1) ◽  
pp. 25-33
Author(s):  
Xinhua Wang ◽  
Peng Yin ◽  
Yukai Gao ◽  
Lei Guo ◽  
◽  
...  
Keyword(s):  
Recommender System ◽  
User Behavior ◽  
Geographical Location ◽  
User Preferences ◽  
Dynamic Features ◽  
Fusion Model ◽  
User Interest ◽  
Location Factors ◽  
User Behavior Analysis ◽  
Real World Datasets

A recommender system is an important tool to help users obtain content and overcome information overload. It can predict users’ interests and offer recommendations by analyzing their history behaviors. However, traditional recommender systems focus primarily on static user behavior analysis. Recently, with the promotion of the Netflix recommendation prize and the open dataset with location and time information, many researchers have focused on the dynamic characteristics of the recommender system (including the changes in the dynamic model of user interest), and begun to offer recommendations based on these dynamic features. Intuitively, these dynamic user features provide us with an effective method to learn user interests deeply. Based on the observations above, we present a dynamic fusion model by integrating geographical location, user preferences, and the time factor based on the Gibbs sampling process to provide better recommendations. To evaluate the performance of our proposed method, we conducted experiments on real-world datasets. The experimental results indicate that our proposed dynamic recommender system with fused time and location factors not only performs well in traditional scenarios, but also in sparsity situations where users appear at the first time.

scholarly journals Movie Recommendation through Multiple Bias Analysis

2021 ◽  
Vol 11 (6) ◽  
pp. 2817
Author(s):  
Tae-Gyu Hwang ◽  
Sung Kwon Kim
Keyword(s):  
Decision Making ◽  
Recommender System ◽  
Real World ◽  
Matrix Factorization ◽  
User Preferences ◽  
Improve Performance ◽  
Bias Analysis ◽  
Useful Knowledge ◽  
Existing Problems ◽  
Movie Recommendation

A recommender system (RS) refers to an agent that recommends items that are suitable for users, and it is implemented through collaborative filtering (CF). CF has a limitation in improving the accuracy of recommendations based on matrix factorization (MF). Therefore, a new method is required for analyzing preference patterns, which could not be derived by existing studies. This study aimed at solving the existing problems through bias analysis. By analyzing users’ and items’ biases of user preferences, the bias-based predictor (BBP) was developed and shown to outperform memory-based CF. In this paper, in order to enhance BBP, multiple bias analysis (MBA) was proposed to efficiently reflect the decision-making in real world. The experimental results using movie data revealed that MBA enhanced BBP accuracy, and that the hybrid models outperformed MF and SVD++. Based on this result, MBA is expected to improve performance when used as a system in related studies and provide useful knowledge in any areas that need features that can represent users.

scholarly journals Accuracy improvements for cold-start recommendation problem using indirect relations in social networks

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fu Jie Tey ◽  
Tin-Yu Wu ◽  
Chiao-Ling Lin ◽  
Jiann-Liang Chen
Keyword(s):  
Social Media ◽  
Recommender System ◽  
Mobile Networks ◽  
Reference Value ◽  
User Preferences ◽  
Digital Information ◽  
Internet Applications ◽  
Social Media Networks ◽  
Recommendation Accuracy ◽  
Gain Access

AbstractRecent advances in Internet applications have facilitated information spreading and, thanks to a wide variety of mobile devices and the burgeoning 5G networks, users easily and quickly gain access to information. Great amounts of digital information moreover have contributed to the emergence of recommender systems that help to filter information. When the rise of mobile networks has pushed forward the growth of social media networks and users get used to posting whatever they do and wherever they visit on the Web, such quick social media updates already make it difficult for users to find historical data. For this reason, this paper presents a social network-based recommender system. Our purpose is to build a user-centered recommender system to exclude the products that users are disinterested in according to user preferences and their friends' shopping experiences so as to make recommendations effective. Since there might be no corresponding reference value for new products or services, we use indirect relations between friends and “friends’ friends” as well as sentinel friends to improve the recommendation accuracy. The simulation result has proven that our proposed mechanism is efficient in enhancing recommendation accuracy.

scholarly journals A Hybrid Knowledge-Based Recommender for Product-Service Systems Mass Customization

Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 296
Author(s):  
Laila Esheiba ◽  
Amal Elgammal ◽  
Iman M. A. Helal ◽  
Mohamed E. El-Sharkawi
Keyword(s):  
Recommender System ◽  
Mass Customization ◽  
Constraint Satisfaction Problem ◽  
Service Systems ◽  
Prototype System ◽  
Knowledge Based ◽  
Product Service ◽  
Wide Range ◽  
Hybrid Knowledge ◽  
Product Service Systems

Manufacturers today compete to offer not only products, but products accompanied by services, which are referred to as product-service systems (PSSs). PSS mass customization is defined as the production of products and services to meet the needs of individual customers with near-mass-production efficiency. In the context of the PSS mass customization environment, customers are overwhelmed by a plethora of previously customized PSS variants. As a result, finding a PSS variant that is precisely aligned with the customer’s needs is a cognitive task that customers will be unable to manage effectively. In this paper, we propose a hybrid knowledge-based recommender system that assists customers in selecting previously customized PSS variants from a wide range of available ones. The recommender system (RS) utilizes ontologies for capturing customer requirements, as well as product-service and production-related knowledge. The RS follows a hybrid recommendation approach, in which the problem of selecting previously customized PSS variants is encoded as a constraint satisfaction problem (CSP), to filter out PSS variants that do not satisfy customer needs, and then uses a weighted utility function to rank the remaining PSS variants. Finally, the RS offers a list of ranked PSS variants that can be scrutinized by the customer. In this study, the proposed recommendation approach was applied to a real-life large-scale case study in the domain of laser machines. To ensure the applicability of the proposed RS, a web-based prototype system has been developed, realizing all the modules of the proposed RS.

scholarly journals A Geospatial database of gastric cancer patients and associated potential risk factors including lifestyle and air pollution

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fatemeh Hashemi Amin ◽  
Mahtab Ghaemi ◽  
Sayyed Mostafa Mostafavi ◽  
Ladan Goshayeshi ◽  
Khadijeh Rezaei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Cancer Patients ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Dietary Habits ◽  
Age Groups ◽  
Geographical Location ◽  
Geographical Information ◽  
Point Feature

Abstract Objectives Gastric cancer (GC) is a multifactorial disease and the fifth most frequent diagnosed cancer worldwide. It accounts for one third of cancer-related mortalities. Geospatial analysis using geographical information systems (GIS) can provide an efficient solution to identify spatial disparities associated with GC. As such, GIS enables policymakers to control cancer in a better way and identify the regions where interventions are needed. This study aims to publish a comprehensive dataset, which was applied to conduct a spatial analysis of GC patients in the city of Mashhad, Iran. Data description We provide a personal geodatabase, a Microsoft Access database that can store, query, and manage both spatial and non-spatial data, which contains four feature classes. “Male_Stomach_Cancer_Patients” and “Female_Stomach_Cancer_Patients” are point feature classes, which show the age and geographical location of 1156 GC cancer patients diagnosed between 2014 and 2017. “Air_Polution_Mashhad” is another point feature class that reveals the amount of six air pollutants, which was taken from Mashhad Environmental Pollutants Monitoring Center between 2017 and 2018. Finally, “Stomach_Cancer_and_Risk_Factors” is a polygon feature class of neighborhood division of Mashhad, consisting of contributor risk factors including dietary habits, smoking, alcohol use, body mass index and population by age groups for all 165 city neighborhoods.

Modelling trust networks using resistive circuits for trust-aware recommender systems

2016 ◽  
Vol 43 (1) ◽  
pp. 135-144 ◽  
Author(s):  
Mehdi Hosseinzadeh Aghdam ◽  
Morteza Analoui ◽  
Peyman Kabiri
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Recommender System ◽  
Cold Start ◽  
User Preferences ◽  
Item Selection ◽  
Trust Networks ◽  
Trust Inference ◽  
Trust Information

Recommender systems have been widely used for predicting unknown ratings. Collaborative filtering as a recommendation technique uses known ratings for predicting user preferences in the item selection. However, current collaborative filtering methods cannot distinguish malicious users from unknown users. Also, they have serious drawbacks in generating ratings for cold-start users. Trust networks among recommender systems have been proved beneficial to improve the quality and number of predictions. This paper proposes an improved trust-aware recommender system that uses resistive circuits for trust inference. This method uses trust information to produce personalized recommendations. The result of evaluating the proposed method on Epinions dataset shows that this method can significantly improve the accuracy of recommender systems while not reducing the coverage of recommender systems.

Specialty Space: Breast Care Centers

2021 ◽  
pp. 193758672199056
Author(s):  
Diane Guevara
Keyword(s):  
Design Process ◽  
Interior Design ◽  
Care Center ◽  
Geographical Location ◽  
Design Guidelines ◽  
Relevant Evidence ◽  
The World ◽  
Hospital Gowns ◽  
Breast Care ◽  
Color Scheme

As background, breast care centers around the world vary in interior design based on geographical location and the trends of the healthcare design process at the time of construction. However, at the forefront of healthcare interior design is the evidence-based design (EBD) process and the Universal Design (UD) guidelines. The Center for Health Design states that the EBD process differs from the linear design process, in that EBD uses relevant evidence to educate and guide the design decisions. The objective of this study was to support future EBD and UD use in the development of patient areas in breast care center interior design. The methods for this study incorporated an extensive review of the literature, examples of eight breast care centers around the world, observations, an interview, and a staff survey concerning the interior design of a local breast care center. The results revealed that using the EBD process and UD, to develop guidelines for patient areas in breast care centers’ interior design, directors could use guidelines to evaluate existing breast care centers or preconstruction for new breast care centers. This study concluded with design guidelines for patient areas in breast care center interior design. The recommended guidelines targeted the following features: robes (vs. hospital gowns), spa-like atmosphere, monochromatic color scheme, use of wood and stone, private check-in areas, wayfinding, room temperature comfort, seating comfort, seating style choices including bariatric, personal items storage, access to natural light, indirect artificial lighting, living plants, views of nature, flooring comfort, and wheelchair accessibility.

scholarly journals SISTEM INFORMASI GEOGRAFIS WILAYAH RAWAN BANJIR DI KOTA PEKANBARU

2019 ◽  
Vol 4 (2) ◽  
pp. 109-119
Author(s):  
Luluk Elvitaria Elvitaria ◽  
Miftahul Khasani
Keyword(s):  
Geographical Information Systems ◽  
Geographical Location ◽  
Geographical Information ◽  
Daily Activities ◽  
Flood Events ◽  
Rain Intensity ◽  
The City ◽  
Term Rain ◽  
Flood Prone Areas

Based on the geographical location of Pekanbaru City is one of the areas included in flood-prone areas, even said that the city of Pekanbaru is included in the red zone related to flooding, seeing from the majority of the existing area is the rawah and river banks. The National Flood Mitigation Agency (BNPB) noted that the city of Pekanbaru is one of the flood-prone cities on the island of Sumatra. In addition to determining flood-prone areas for the Regional BPBD Office in Pekanbaru City, the community also wants to know the location that often floods and determine the long-term rain intensity capacity that will cause flooding, so that it does not hinder the daily activities. To deal with this problem, a Geographical Information System needs to be developed that can determine areas that often occur in natural flooding. Geographical information systems are expected to be able to assist the BPBD Office in managing flood data that has occurred in the city of Pekanbaru, and help provide information about floods that are needed by the community to anticipate further flood events.  

scholarly journals PEMETAAN KANTOR POLISI KABUPATEN SITUBONDO BERBASIS PETA

2018 ◽  
Vol 3 (2) ◽  
pp. 227-234
Author(s):  
Ahmad Rofiqi
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Information Exchange ◽  
Geographical Location ◽  
Geographical Information ◽  
The Public ◽  
Police Station

Situbondo Regional Police are law enforcers who work in the East Java Situbondo district. Of course, in carrying out all its duties, it requires communication and information exchange between officers and civilians to carry out police duties properly and effectively. In reality on the ground, not all Situbondo people, especially those outside Situbondo, know the geographical location of the police station in each sub-district in Situbondo district. The only way to find the Situbondo Police Station is to ask and ask someone who has visited or learned about the office. However, using this procedure requires more time and is a bit of a hassle for other people, this is due to the absence of a map pointer to deliver or give an overview of the location of the Police station. From the above problems, namely the absence of loyal Police station appointees at all times to help, it is necessary to design a Situbondo Police Station Geographical Information System that is the answer to the problems discussed above. The establishment of this system is expected to be able to assist the Police in informing the geographical location of the Police station along with important information and also assisting the public in finding the Police station quickly and effectively.

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