OSU AIM ASSIST DOWNLOAD HOW TO
Resolving how to integrate the system with existing library systems is currently addressed by keeping SERF separate from regular library systems. Using the OSU Libraries web site as a test bed presents various challenges. Since CF depends on user input or activity to learn, CF research requires real-world test-beds with active communities of users. Ultimately, in addition to their searching function, search systems become tools for shaping resources and services collected. Increased access elevates the importance of the Libraries, both their collections and their services, while improving patrons’ searching experiences. They will be more accessible in terms of time spent searching and relevancy to a user’s need. The shared premise of the OSU Libraries and EECS is that by enabling the entire community of users to participate in organizing and recommending information, the libraries’ resources will increase in value. By matching information contexts, the system learns from the experience of the first person’s to express the need and find resources for later users of the library. SERF addresses how the library can assist multiple people with similar information needs locate appropriate information.
On the other end of the spectrum, researchers in the biological sciences may have differing specialties, but would use similar resources. For example, 300 students in a first year writing class would all need the same types of materials if we can learn those needs by observing the first few students, then later students should be directed to the useful resources easily. While each user may have different information needs every time the library is used, groups of users have similar information needs. User profiles capture past interests and demographics if the user elects to maintain a login and profile. A user’s query indicates the immediate information need. An information context takes into account the user’s immediate information need as well as past interests and even demographics. SERF’s goal is to match information contexts rather than users. This traditional CF approach does not work in the library setting where the needs of users can be different every time they come into the library environment. Consequently, these systems can match users with similar interests by simply comparing two users’ historical profiles.
OSU AIM ASSIST DOWNLOAD MOVIE
People using a movie recommendation system will always be looking for a movie and their preferences will remain quite constant. Traditional CF applications assume that users have fairly consistent information needs over time.
An experimental prototype of SERF is currently available to all users of the OSU Libraries web site. To find similar information needs, queries are compared using a keyword matching technique. emailing the page or the last page viewed). a vote), or some user activity that implies that a resource is useful (e.g. The system determines that resources are relevant to a question by observing either an explicit user statement that the resource is valuable (e.g. If previous users have issued similar queries, then SERF recommends documents, sites, or databases that those previous users found relevant and useful. Users are encouraged, but not required, to enter grammatically correct, complete sentences. In SERF, a user issues a question or a statement of the current information need (e.g.
The setting can be used to learn by observing patrons and react to their responses. complex with content targeted at multiple and diverse users.