3) Belkin: Anomalous states of knowledge as a basis for information retrieval.

In "Anomalous states of knowledge as a basis for information retrieval," Belkin, Oddy, and Brooks describe the results of their study for the British Library Research and Development Department on the interaction of users with the systems on which they searched with a focus on ASKs. They concluded that that best-match answering system, which was information retrieval (IR) systems’ primarily means of organizing retrieved answers, was not an efficient way of attempting to resolve a user’s ASK and that an ASK-match system would be more appropriate (Belkin 1982, pg. 61).

ASK, or anomalous states of knowledge, is when a person realizes that there is a gap or anomaly in his or her knowledge (Belkin 1982, pg. 62). Belkin's ASK hypothesis is that an information need is created when a person realizes that he or she has a gap or anomaly, and attempts to fill or fix it through communication - In the terms of information retrieval, this achieved with the help of an information system. To connect to the other reading from this week, an ASK is similar to the information need described by Taylor. In Taylor's "Question negotiation and information seeking in libraries," he describes how a user or patron develops, with a librarian's aid, an indistinct desire for information into a searchable question (Taylor 1968, pg. 31). This first stage of information need can be the result of an ASK: a user is aware that s/he needs to know more about a topic and begins the process of resolving that need. Returning to Belkin, because IRs returned a best-match answer, that is, the “best possible… representation [that] most closely matches… a representation of a request for information” (Belkin 1982, pg. 63). According to Belkin, this method has two substantial weaknesses: the user may not be able to articulate his or her specific need in a pithy query capable of being entered into the IR system and because of this, the information retrieved may not be relevant (Belkin 1982, pg. 63). I can't help but think that Belkin, as well as some of our other readings, are just explaining the obvious. While I agree that IR systems are sometimes overly simplistic in their approaches to searching, I feel like Belkin et al. aren't doing much but stating the obvious.

An IR system able to uncover the user’s real information need would serve as a better model, according to Belkin. The IR should help the person solve the problem, not solve it for him/her. While this might be an ideal model, this article shows its age by dismissing best match. Much progress has been made since 1982, and Google, by far the most popular search system, currently utilizes best-match retrieval with great success. Also, I think that best match can be helpful: if you don't know what exactly you're looking for, the computer's retrieved results (and its interpretation of what you meant) might help you better define your need.