Information Delivery Systems:An Exploration of Web Pull and Push Technologies

Abstract

The Web is alive with news stories, pictures, music, and videos. How will organizations, managers, and other users find out what content is available, then locate it, analyze it, and make it meaningful? In this tutorial, we identify and classify eight types of information delivery systems (IDS) that we refer to as alpha, beta, gamma and delta and push technologies. For pull technologies we explain "surfing the Web", search engines, spiders and bots, personal agents, and finally evolutionary agents. For push technologies we explain Webcasting, channels and subscriptions, and data mining methods for determining preferences and filtering topics. We also examine the role of the evolutionary agents in push technologies. Throughout the paper, we provide examples of current pull and push technologies in each of the categories for pull and push. We include both personal and corporate applications. We then examine the managerial and social implications of higher-level IDS and suggest what is in store for users of information delivery systems in the future.

Intelligent spider for information retrieval to support mining-based price prediction for online auctioning

“…This investigation is concerned with ''the functions of the spiders''. Many previous studies have already defined and Table 1 summarizes these definitions (Ali & McRoy, 2000;Chen et al, 2002;Green & Pant, 1999;Kendall & Kendall, 1999;Miller & Bharat, 1998). Base on previous research, spiders are developed to navigate, retrieve and filter useful information on the web sites for the user.…”

“…On the other hand, an intelligent agent can be developed by pull technology. Kendall (Kendall & Kendall, 1999) defines pull technologies in four levels: Alpha-pull, Beta-pull, Gamma-pull and Delta-pull (see Table 2). The purpose of information retrieval of users moves from ''feel they want'' to ''really need''.…”

“…They have been called on-line pseudo people, cited as popular test beds for multiple aspects of AI; labeled as intelligent on-line assistants and group negotiators Kendall and Kendall (1999) Search engines are a simple example; typically they make use of a program (called a spider) that traverses the Web and creates databases of the keywords in a Web page (allowing fast, local retrieval of these resources) Ali and McRoy (2000) Internet spiders (a.k.a. crawlers), have been used as the main program in the backend of most search engines.…”

“…Based on the definition of ''spiders'' by Kendall and Kendall (1999), a superior agent or spider should understand the user, and then adapts over time based on the need of customers. Unfortunately, no existing spider can comprehend customer behavior.…”

Web Contents Tracking by Learning of Page Grammars

“…Therefore, data obtained from the Web e.g. by crawler systems are mainly accessed by applying pull technologies [10]. The basic problem in this case is the missing knowledge about the times of data changes at the client side.…”