Papers by Bandar Mohammed
Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics, 2018
Developing intelligent and interactive systems with visual user interfaces is essential for any w... more Developing intelligent and interactive systems with visual user interfaces is essential for any website and mobile device. In this study, we propose a new web-based shopping system to elicit buyer's requirements and preferences and to provide a set of suggestions accordingly. This process is achieved by first representing the elicited information through graphical models and then solving the underlying constrained problem. More precisely, we have used the Weighted CP-nets (WCP-net) graphical model to allow the user to express finegrained preferences on the product attributes and their values in a quantitative or a conditional qualitative form. The latter has been extended in this paper to include constraints between attributes. A backtrack search algorithm is then performed to solve the constrained WCP-net and to return a set of Pareto optimal solutions satisfying all the constraints and maximizing all the preferences.
In many online systems, online shoppers are usually overwhelmed by a huge number of outcomes or c... more In many online systems, online shoppers are usually overwhelmed by a huge number of outcomes or choices. However, in practice, they usually have interest in only a small subset of choices. In order to narrow down the huge number of available items, these users provide a set of preferences over the outcomes. Therefore, such systems must take user preferences into consideration when looking for the optimal outcome. This paper studies the problem of deciding which item is the most preferred given the user preferences in an online shopping website. We study the problem of co-existence between problem requirements and user preferences. We assume that the preferences can be expressed in a quantitative (numerical) way, in a qualitative (ordinal) way or both.
Lecture Notes in Computer Science, 2015
Constraints and preferences coexist in a wide variety of real world applications. In a previous w... more Constraints and preferences coexist in a wide variety of real world applications. In a previous work we have proposed a preference-based online shopping system that handles both constraints as well as preferences where these latter can be in a qualitative or a quantitative form. Given online shoppers' requirements and preferences, the proposed system provides a set of suggested products meeting the users' needs and desires. This is an improvement to the current shopping websites where the clients are restricted to choose among a set of alternatives and not necessarily those meeting their needs and satisfaction. For a better management of constraints and preferences, we extend in this paper the well known constrained CP-Net model to quantitative constraints and integrate it into our system. This extended constrained CP-Net takes a set of constraints and preferences expressing user's requirements and desires, and returns a set of outcomes provided in the form of list of suggestions. This latter list is sorted according to user's preferences. An experimental evaluation has been conducted in order to assess the time efficiency of the proposed model to return the list of suggestions to the user. The results show that the response time is acceptable when the number of attributes is of manageable size.
2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
Designing interactive systems with graphic user interfaces is an important step in the developmen... more Designing interactive systems with graphic user interfaces is an important step in the development of online devices and websites. Online shopping systems and recommender applications have improved in the last decade and they are now widely used all over the world. However, it is important to understand online shoppers needs and preferences and to take them into account. In this regard, several online shopping systems rely on customer preference elicitation while others suggest products based on other customers recommendations. The focus of this paper is the interaction design of a system for Managing Preferences and Constraints (MPC) and Preferences Learning (PL). An evaluation method is utilized to obtain user feedback on how effective the system is and how easy it is to use, compared to other systems. The Volere requirements specification template was used with the six step framework to guide the evaluation.
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012
ABSTRACT In many online systems, shoppers are usually overwhelmed by a huge number of outcomes an... more ABSTRACT In many online systems, shoppers are usually overwhelmed by a huge number of outcomes and choices. In practice however, they usually have interest in only some of these choices. While these online shopping systems allow the users to provide some keywords and other information in order to filter and get only what they need, these latter feel that what they get does not necessarily meet their satisfaction. In this paper, we propose a new shopping system that enables the customers to express what they want when buying a product online. More precisely, the users are given the ability to provide their requirements and desires in a friendly and interactive way. The system will then provide a list of suggestions meeting the users' requirements and maximizing their desires. Requirements and desires are managed, in a unique model, respectively as a set of hard constraints and preferences where these latter can be quantitative (numerical), qualitative (ordinal) or both. The branch and bound method is then applied in order to provide the users with a list of best outcomes.
Computer and Information Science, 2012
Preference Elicitation is very important for online shopping interactive applications. The potent... more Preference Elicitation is very important for online shopping interactive applications. The potential buyers usually have interest in some of the attributes of the product they want to purchase. While the current online shopping systems allow the users to provide some keywords and other information in order to filter and get only what they need, these latter feel that what they get does not necessarily meet their satisfaction. In this paper, we propose a new shopping system that enables the customers to express their needs when buying a product online. More precisely, the users are given the ability to provide their requirements and desires in a friendly and interactive way. The system will then provide a list of suggestions meeting the users' requirements and maximizing their desires. Requirements and desires are managed, in a unique model, respectively as a set of hard constraints and preferences where these latter can be quantitative (numerical), qualitative (ordinal) or both. These constraints and preferences represent a constraint optimization problem where optimal solutions (best outcomes) are those satisfying the hard constraints and maximizing the user's preferences. The branch and bound method is applied in order to provide the user with a list of best outcomes.
Computer and Information Science, 2013
The importance of implementing recommender systems has significantly increased during the last de... more The importance of implementing recommender systems has significantly increased during the last decade. The majority of available recommender systems do not offer clients the ability to make selections based on their choices or desires. This has motivated the development of a web based recommender system in order to recommend products to users and customers. The new system is an extension of an online application previously developed for online shopping under constraints and preferences. In this work, the system is enhanced by introducing a learning component to learn user preferences and suggests products based on them. More precisely, the new component learns from other customers' preferences and makes a set of recommendations using data mining techiques including classification, association rules and cluster analysis techniques. The results of experimental tests, conducted to evaluate the performance of this component when compiling a list of recommendations, are very promising.
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Papers by Bandar Mohammed