A Product Recommendation System Based On Mobile Context

The mobile application is developed using Android Studio SDK. All the CRUD operations are performed in MySQL database present in Amazon cloud. To connect the UI with the database, PHP scripting language is used and the PHP files are accessed from the remote server via HTTP request methods.

Now our service is to acquire the user who has the most likelihood to be recommended. First we use the probability function $P(r,u)$ using the communication between the user and recommender. If the probability is higher than our defined threshold value then grouped the user. All the nodes in this group are our expected nodes. Now for the nearest one we run BFS and extract the best one for recommendation.

The role of mother during 1970’s was to take care of the family, not by money, but emotional and physical help. Whether that be taking care of the family when they were sick or maintain the house by cleaning. It was also a time in which women's voices and opinions were drowned out by their demanding husband for another beer. Edith Bunker from All in the Family followed these roles and stereotypes to a “T”.

A linear formula idea will be used and the decision variables will be labeled as follow:

The first step taken was measuring the interest of the market for such an app. We published an online survey to substantiate whether our idea was appealing to our market segmentation, which is both, men and women, from 18 to 65 years old with an interest in street food and residing in the Miami area. The results of this survey was encouraging.

- Macys is the world largest department store in the world, it recently announced the pilot of Macys “on call” , and this is basically a mobile tool that essentially allows customers to interact with an al-powered platform through their mobile devices. This tool is control and influenced by IBM watson and is set to be tested in 10 new locations around the U.S. This gadget allows customers input natural language questions regarding the products of each store regionally. They would then receive a response based on their inquiry. For example, if I was looking for a specific sports gear, and they did not have any available, I would then use this tool and it would locate exactly where to find them as well as indicating the quantity on hand. Macys

Instead of various local chain stores, Netflix operated from a single virtual store that offered customers new rental features. The web services platform utilized customization and a user-friendly design to facilitate renting movies. “CineMatch,” a proprietary developed application, tailored the virtual store to each subscriber. This technology produced customized rental suggestions for customers while maximizing potential inventory. “CineMatch” incorporated a subscriber rating system of past rentals to generate more efficient and personalized future recommendations. The web-based services also improved selection through the ability to easily browse Netflix’s large inventory catalog and add selections to a personalized “Queue,” which lists movies customers have scheduled to receive. Instead of being forced to navigate through the traditional genre and alphabetized catalog, Netflix offered an easier movie selection process. Besides the selection efficiencies, members have the ability to share ratings, reviews, and movie selections with each other through the “Community” feature.

The question of when is it justified to disclose patient confidentiality depends on the risks associated. Keeping of patients’ records remains important to any clinical officer. The CMA code of ethics advices the keeping of patient’s personal health information private and can only be released to the third party as outlined by law (Fowler, 2008). In the case study, patient’s confidentiality has been put to test in that there first existed keeping of the patient records confidential and proper treatment was offered but this has been betrayed. The forgery of the record and refused to cooperate with the patient poses a threat to the recovery of the correct information necessitating reporting the case to the police; acting according to the state

Smart phone apps and e-diaries have become much more accessible and easy to use throughout the years. We are currently experiencing a technological boom with the development of smart phone apps and user friendly e-diaries for data collection. Due to the transient nature of society,

But now, McDonald 's was combined with Yahoo establish the website in order to solve the problem of large logistics management, that is to provide information system access for its staff, chain stores and suppliers in all over the world. This website cover 120 countries, and at the same time when customers into the website, they can check every country and every outlets. In conclusion, the success of McDonald

line with the existent nature of McDonald's premises and business model. Thus, it is recommendable to

Mobile computing has infiltrated every area of our planet and personal lives. We have become so dependent upon our mobile devices they are often referred to as our third limb. Regardless of race, color, creed or location, mobile technology has shrunk the entire world into the palm of our hands. Mobile technology has made research, communication with our friends and family, education, entertainment and even banking possible to do on the go.

Recommender Systems are based on well-structured and incremental algorithms that have different strengths and weaknesses \cite{ricci2011introduction}. In general, the main existing RSs are concerned with improving accuracy with the premise of being useful to users. In this context, there is an increasing number of custom techniques that analyze the profile of the target user in order to better satisfy them \cite{bobadilla2013recommender}. In this sense, we conducted a broad study of the several metrics used in the literature to evaluate RSs. By organizational purposes, we divided these metrics into three groups: {\it Effectiveness-based}, {\it Complementary Dimensions of Quality} and {\it Domain Profiling}.\looseness=-1

Various techniques have been used in content-based models. Such systems try to find regularities in the descriptions that can be used to distinguish highly rated items from others [97]. Content-based approaches are based on objective information about the items. This information is automatically extracted from various sources (e.g., Web pages) or manually introduced (e.g., product database). However, selecting one item or another is based mostly on subjective attributes of the item (e.g., a well-written document or a product with a spicy taste). Therefore, these attributes, which better influence the user’s choice, are not taken into account. In the rest of this section, we discuss three technique of content-based filtering technique including keyword-based models, semantic techniques, and probabilistic models. The first systematic evaluation of the impact of applying perturbation-based privacy technologies on the usability of content-based recommendation systems proposed by Puglisi, S., et al. (2015) [98]. The primary goal of their work is to investigate the effects of tag forgery to the content-based recommendation in a real-world application scenario, studying the interplay between the degree of privacy and the potential degradation of the quality of the recommendation. In other paper, Rana, C. and S.K. Jain [23] have developed a book recommendation system that is based on content-based recommendation technique and takes into account the choices of not an

A fiber optic cable is a network cable that contains strands of glass fibers within an insulated casing. There are designed for very high-performance data networking, long distance and telecommunications. Compare with wired cables, fiber optic cables give higher bandwidth and can transmit data over longer distances. Fiber optic cables support world's internet, telephone systems and cable television.