Comparison Shopping

This chapter introduces the shopping agent technology as a new Internet marketing trend. The recent development of shopping agent Web sites has offered online shoppers an excellent comparative shopping environment. Shopping agent Web sites, also called shopping agents or shopping bots, are software programs that search the Internet stores on the Web and find products that meet a buyer’s specifications. Not only do these agent Web sites bring comparative product and price information from individual merchants’ Web sites, but also provide the online merchant ratings to customers. In summary, these agent Web sites take a query, search the Web sites of individual merchants that may have the product sought, bring back the results, and present them in a consolidated and compact format that allows comparison shopping at a glance.

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The Next Generation of Shopbots

Comparison-Shopping Services and Agent Designs ◽

10.4018/978-1-59904-978-6.ch002 ◽

2011 ◽

pp. 19-36 ◽

Cited By ~ 1

Author(s):

Maria Fasli

Keyword(s):

Decision Making ◽

Web Services ◽

Semantic Web ◽

Online Shopping ◽

Vast Number ◽

High Expectations ◽

Profound Impact ◽

Comparison Shopping ◽

Shopping Experience ◽

Immense Potential

The huge growth of e-commerce has had a profound impact on users who can now choose from a vast number of options online. Inevitably, as the number of choices has increased, so has the need for tools to help users organize, manage and utilize information on these for better decision-making. Comparison shopping agents or shopbots can help users decide what to buy and enhance their online shopping experience. However, despite the high expectations, the immense potential of shopbots has not been fully realized. In this chapter, the author identifies the limitations and drawbacks of current shopbots, in particular, with regard to the underlying technology for building such systems. She then discusses how these technical limitations can be overcome by making use of the Semantic Web and Web Services. She also considers how shopbots can truly serve the user by providing personalized, impartial and flexible services.

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Learning Information Extraction Rules for Web Data Mining

Encyclopedia of Data Warehousing and Mining ◽

10.4018/978-1-59140-557-3.ch129 ◽

2011 ◽

pp. 678-683

Author(s):

Chia-Hui Chang ◽

Chun-Nan Hsu

Keyword(s):

Information Extraction ◽

Web Mining ◽

World Wide ◽

Information Sources ◽

Structured Data ◽

Comparison Shopping ◽

Data Formats ◽

The World ◽

Document Collection ◽

Keyword Searching

The explosive growth and popularity of the World Wide Web has resulted in a huge number of information sources on the Internet. However, due to the heterogeneity and the lack of structure of Web information sources, access to this huge collection of information has been limited to browsing and keyword searching. Sophisticated Web-mining applications, such as comparison shopping, require expensive maintenance costs to deal with different data formats. The problem in translating the contents of input documents into structured data is called information extraction (IE). Unlike information retrieval (IR), which concerns how to identify relevant documents from a document collection, IE produces structured data ready for post-processing, which is crucial to many applications of Web mining and search tools.

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