Users’ Decision Behavior in Recommender Interfaces: Impact of Layout Design

نویسندگان

  • Li Chen
  • Ho Keung Tsoi
چکیده

Recommender systems have been increasingly adopted in the current Web environment, to facilitate users in efficiently locating items in which they are interested. However, most studies so far have emphasized the algorithm’s performance, rather than from the user’s perspective to investigate her/his decision-making behavior in the recommender interfaces. In this paper, we have performed a user study, with the aim to evaluate the role of layout designs in influencing users’ decision process. The compared layouts include three typical ones: list, grid and pie. The experiment revealed significant differences among them, with regard to users’ clicking behavior and subjective perceptions. In particular, pie has been demonstrated to significantly increase users’ decision confidence, enjoyability, perceived recommender competence, and usage intention.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Eye-Tracking Study of User Behavior in Recommender Interfaces

Recommender systems, as a type of Web personalized service to support users’ online product searching, have been widely developed in recent years but with primary emphasis on algorithm accuracy. In this paper, we particularly investigate the efficacy of recommender interface designs in affecting users’ decision making strategies through the observation of their eye movements and product selecti...

متن کامل

Increasing the Accuracy of Recommender Systems Using the Combination of K-Means and Differential Evolution Algorithms

Recommender systems are the systems that try to make recommendations to each user based on performance, personal tastes, user behaviors, and the context that match their personal preferences and help them in the decision-making process. One of the most important subjects regarding these systems is to increase the system accuracy which means how much the recommendations are close to the user int...

متن کامل

A social recommender system based on matrix factorization considering dynamics of user preferences

With the expansion of social networks, the use of recommender systems in these networks has attracted considerable attention. Recommender systems have become an important tool for alleviating the information that overload problem of users by providing personalized recommendations to a user who might like based on past preferences or observed behavior about one or various items. In these systems...

متن کامل

Design a Hybrid Recommender System Solving Cold-start Problem Using Clustering and Chaotic PSO Algorithm

One of the main challenges of increasing information in the new era, is to find information of interest in the mass of data. This important matter has been considered in the design of many sites that interact with users. Recommender systems have been considered to resolve this issue and have tried to help users to achieve their desired information; however, they face limitations. One of the mos...

متن کامل

Towards understanding how users decide about friendship requests in Online Social Networks

Accepting friend requests from strangers in Facebook-like online social networks is known to be a risky behavior. Still, empirical evidence suggests that Facebook users often accept such requests with high rate. As a first step towards technology support of users in their decisions about friend requests, we investigate why users accept such requests. We conducted two studies of users’ befriendi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011