Intelligent Personalization Agent for Product Brokering

Intelligent Personalization Agent for Product Brokering

Sheng-Uei Guan (Brunel University, UK)
DOI: 10.4018/978-1-60566-014-1.ch095
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A good business to consumer environment can be developed through the creation of intelligent software agents (Guan, Zhi, & Maung, 2004; Soltysiak & Crabtree, 1998) to fulfill the needs of consumers patronizing online e-commerce stores (Guan, 2006). This includes intelligent filtering services (Chanan, 2001) and product brokering services (Guan, Ngoo, & Zhu, 2002) to understand a user’s needs before alerting the user of suitable products according to his needs and preference. We present an approach to capture user response toward product attributes, including nonquantifiable ones. The proposed solution does not generalize or stereotype user preference but captures the user’s unique taste and recommends a list of products to the user. Under the proposed approach, the system is able to handle the inclusion of any unaccounted attribute that is not predefined in the system, without reprogramming the system. The system is able to cater to any unaccounted attribute through a general description field found in most product databases. This is useful, as hundreds of new attributes of products emerge each day, making any complex analysis impossible. In addition, the system is selfadjusting in nature and can adapt to changes in user preference.
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Although there is a tremendous increase in e-commerce activities, technology in enhancing consumers’ shopping experience remains primitive. Unlike real life department stores, there are no sales assistants to aid consumers in selecting the most appropriate product for users. Consumers are further confused by the large options and varieties of goods available. Thus, there is a need to provide on top of the provided filtering and search services (Bierwirth, 2000) an effective piece of software in the form of a product brokering agent to understand their needs and assist them in selecting suitable products.

A user’s interest in a particular product is often influenced by the product attributes that range from price to brand name. This research classifies attributes as accounted, unaccounted, and detected. The same attributes may also be classified as quantifiable or nonquantifiable attributes.

Accounted attributes are predefined attributes that the system is specially customised to handle. A system may be designed to capture the user’s choice in terms of price and brand name, making them accounted attributes. Unaccounted attributes have the opposite definition, and such attributes are not predefined in the ontology of the system (Guan & Zhu, 2004). The system does not understand whether an unaccounted attribute represents a model or a brand name. Such attributes merely appear in the product description field of the database. The system will attempt to detect the unaccounted attributes that affect the user’s preference and consider them as detected attributes. Thus, detected attributes are unaccounted attributes that are detected to be vital in affecting the user’s preference.

Quantifiable attributes contain specific numeric values (e.g., hard disk size) and thus their values are well defined. Nonquantifiable attributes, on the other hand, do not have any numeric values and their valuation may differ from user to user (e.g., brand name).

Key Terms in this Chapter

User Feedback: Refers to the response from the user to specific prompts or messages given by the system.

Genetic Algorithms: Inspired by evolutionary biology, genetic algorithms are a particular class of evolutionary algorithms that use techniques such as inheritance, mutation, selection, and crossover in problem solving

Personalisation Agent: A software agent that is capable of learning and responding to user needs.

Software Agent: A piece of software that acts on behalf of a user in carrying out specific tasks specified by the user.

Ontology: The study of being or existence. It defines entities and their relationships within a certain framework.

E-Commerce: Consists primarily of the distributing, buying, selling, marketing, and servicing of products or services over electronic systems such as the Internet and other computer networks

Product Broker: A product broker is a party that mediates between a buyer and a seller some specific product.

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