Intelligent Automation, Inc., Rockville, MD 20850, U.S.A.
firstname.lastname@example.org and email@example.com
Traditional navigation ignores an individual's specific preferences, needs, or other abilities (e.g., reading level). This can be particularly problematic when the user is under time, or learning and comprehension constraints, as in educational situations. An alternative is automated guidance toward material that is of interest, contextually relevant, and appropriate for the user. In an educational setting it would be useful for a learner to be guided along a path of Web resources which meet his or her educational needs. In the commercial arena it would be useful to direct the Web user to those products and services in which he or she might be especially interested.
Notable examples of such non-traditional approaches are: Walden's Paths , WebWatcher  and Letizia . These systems have shown some promise, especially in locating pages similar to those already found to be of interest to the user, but stop short of locating Web resources for specific users with specific educational needs and goals. With minimal adaptations and the technology available today, the vast amount of information on the Web can be even better managed and delivered to the meet the user's needs, goals, preferences and attributes. COOL links  are one such adaptation.
Other link types exist for instance multi-ended links and have been implemented in a variety of hypermedia applications, but typically not the Web. At first it seems that a multi-ended link one which "refers" to multiple resources applied to the Web would be ambiguous. To which of the multiple resources is the user taken when the link is clicked?
COOL links are an example of multi-ended, Web links that are not ambiguous. This is accomplished by letting these links "refer" to a collection of resources only until click-time. Then a single resource is selected from the collection by some evaluation scheme. A COOL link could look something like:
<A COOLREF =
- metadata_description_of_resource_A, url_of_resource_A;
- metadata_description_of_resource_B, url_of_resource_B;
- metadata_description_of_resource_N, url_of_resource_N>
The resources associated with a COOL link are unordered. There is no special significance given to those that appear closer to the start of the link description than those that appear nearer the end. Instead, when a COOL link is clicked the metadata of each component resource is evaluated and compared against a separate set of input parameters, for instance the user's profile, and the "best-fit" resource is returned.
Presumably, each distinct resource in a COOL link collection provides different benefits to different users (though each resource may contain information about the same subject or topic). The burden of choosing a link component from the collection is placed upon the browsing tool (or a plug-in) at runtime.
In summary, the four-part COOL link machinery contains: (i)The link itself, (ii)selection algorithm(s), (iii)external input features such as user profiles, and (iv)meta-descriptions of the link's associated resources.
Education: Students tend to progress at their own pace, learn differently, and have a diverse set of skills, even though they are following the same lesson. Ideally, an instructor takes a student's characteristics into account, and teaches accordingly. COOL links can serve as a tool to facilitate lesson individualization in an electronic learning environment. As students navigate Web-based lesson material templates, they can be guided on a path that is most appropriate to their learning goals and capabilities. A link selection mechanism determines a path dynamically as a student browses through courseware containing COOL links. An instructor or lesson developer can create a single lesson plan template which contains different material for use by students with differing needs. Attributes like the pedagogical "appropriateness," associated grade level, and readability index of a resource in relation to a student's profile may weigh heavily on the choices made by the selection mechanism.
User-centric navigation: A great deal of research has been carried out on Web trails, paths and guided tours . Trails tend to be contextually relevant and interesting to the user, but are not necessarily shaped by characteristics of the individual user himself. Taking these characteristics into account leads to user-centric navigation (UCN) the automated guidance of an individual through the Web . UCN is a paradigm shift from the more passive modes of hypertext navigation as it facilitates the development of dynamic trails based upon context, user interaction and user needs.
Advertising, marketing and sales: The colour, size, cost, or style of a particular consumer item in relation to a consumer's preferences may affect his or her desire to purchase an item. Additionally, other attributes of the consumer like background, gender, age, career and income will affect the likelihood of a purchase. With advertising and sales a mainstay of the Web, sellers are looking for ways to direct those most interested in their products to their pages. COOL links, together with user profile data, are one way to accomplish some amount of successful marketing, and in the process eliminate large numbers of unwanted hits.