Savina N.   Ryabko B.   Nechta I.  

Applications of Information Theory and Psychology Laws to Optimization of Internet Search

Reporter: Ryabko B.

The problem of search of the necessary information in Internet and time spent for search becomes very important, because Internet plays important role in all spheres of human life. Especially actuarial this problem is for e-learning and some other human-computer interaction systems where  one of the most important problems is design menus, which are used for presenting, organizing, and selecting information, see [1- 4].
We consider a particular class of problems for which the objects can be arranged in alphabetical order and a user knows the name of the object in advance (it can be name of a city if one is buying  a ticket, the name of a person if one is looking for a telephone number, etc.). For this class of problems a menu could be arranged automatically (i. e. not requiring human participation). We describe a method of menu construction which allows minimization of the average search time. In contrast to the method of the [5], the proposed method of constructing a hierarchical menu is based on a psychological Hick’s law [6] and known codes for data compression. It is shown that the Shannon entropy is the lower limit of the average search time for any menu. In this report we describes a general algorithm, that allows to build a menu whose search time is close to the minimum, but the complexity of the proposed method is high. It makes the discussed problems (first of all, designing more effective general methods for the search and, secondly, for the sub-tasks search, for which fast algorithms could be found) to be very actual. The considered examples have shown that the proposed method allows to build the menu which is close to optimal. Besides, we carried out some experiments which give a possibility to make recommendations for practical applications.

[1] E. Lee,  R. Macgregor, “Minimizing user search time in menu retrieval systems”. Human factors, 27(2),  pp.157-162 (1985).
[2] M. L.  Toms, Using cluster analysis for deriving menu structures for automotive mobile multimedia applications,
(SAE Technical Paper, 2001). 
[3]  M. Danilenko, “Semantic-aware optimization of user interface menus”, Automation and Remote Control,  8,
pp. 1399-1411 (2013).
[4] T. Govindasamy, “Successful implementation of e-Learning Pedagogical considerations”, Internet and Higher Education, 4,  pp. 287-299, (2002).
[5] I.H. Witten,  J.G. Cleary, S. Greenberg, “On frequency-based menu-splitting algorithms”,  International Journal  of Man-Machine Studies, 21(2), pp. 135–148, (1984).
[6] W. E.  Hick, “On the rate of gain of information”, Quarterly Journal of Experimental Psychology, 4, 11-26 (1952).