Effort and accuracy analysis of choice strategies for electronic product catalogs

One crucial task for e-commerce systems is to help buyers find products that not only satisfy their preferences but also reduce their search effort. Usually the amount of available products is far beyond the upper limit that any individual could process by hand; thus product search tools are em-ployed to generate target product(s) by eliciting the buyer’s preferences and then executing some kind of choice strate-gies. We propose in this paper an extended effort–accuracy framework for measuring the performance of various choice strategies in terms of cognitive effort, elicitation effort and decision accuracy. The performance of a variety of basic choice strategies is further studied by theoretical analysis as well as empirical simulations. It shows that the perfor-mance of a given choice strategy is a tradeoff between choice accuracy and effort required from the users. The proposed framework also suggests a new efficient method of evaluat-ing the user interfaces of e-commerce systems by analyzing the performance of the underlying choice strategies. Categories and Subject Descriptor

Effort and accuracy analysis of choice strategies for electronic product catalogs

One crucial task for e-commerce systems is to help buyers find products that not only satisfy their preferences but also reduce their search effort. Usually the amount of available products is far beyond the upper limit that any individual could process by hand; thus product search tools are employed to generate target product (s) by eliciting the buyer's preferences and then executing some kind of choice strategies. We propose in this paper an extended effort-accuracy framework for measuring the performance of various choice strategies in terms of cognitive effort, elicitation effort and decision accuracy. The performance of a variety of basic choice strategies is further studied by theoretical analysis as well as empirical simulations. It shows that the performance of a given choice strategy is a tradeoff between choice accuracy and effort required from the users. The proposed framework also suggests a new efficient method of evaluating the user interfaces of e-commerce systems by analyzing the performance of the underlying choice strategies. Copyright 2005 ACM

Interactive product catalogue with user preference tracking

In the context of m-commerce, small screen size poses serious difficulty for users to browse effectively through a product catalogue, given the limited number of products that may be presented on-screen. Despite the availability of search engines, filters and recommender systems to aid users, these techniques focus on a narrow segment of product offering. The users are thus denied the opportunity to do a more expansive exploration of the products available. This paper describes a novel approach to overcome the constraints of small screen size. Through integration of a product catalogue with a recommender system, an adaptive system has been created that guides users through the process of product browsing. An original technique has been developed to cluster similar positive examples together to identify areas of interest of a user. The performance of this technique has been evaluated and the results proved to be promising

Evaluating product search and recommender systems for E-commerce environments

Online systems that help users select the most preferential item from a large electronic catalog are known as product search and recommender systems. Evaluation of various proposed technologies is essential for further development in this area. This paper describes the design and implementation of two user studies in which a particular product search tool, known as example critiquing, was evaluated against a chosen baseline model. The results confirm that example critiquing significantly reduces users' task time and error rate while increasing decision accuracy. Additionally, the results of the second user study show that a particular implementation of example critiquing also made users more confident about their choices. The main contribution is that through these two user studies, an evaluation framework of three criteria was successfully identified, which can be used for evaluating general product search and recommender systems in E-commerce environments. These two experiments and the actual procedures also shed light on some of the most important issues which need to be considered for evaluating such tools, such as the preparation of materials for evaluation, user task design, the context of evaluation, the criteria, the measures and the methodology of result analyse

ESO Imaging survey: Optical Deep Public Survey

This paper presents new five passbands (UBVRI) optical wide-field imaging data accumulated as part of the DEEP Public Survey (DPS) carried out as a public survey by the ESO Imaging Survey (EIS) project. Out of the 3 square degrees originally proposed, the survey covers 2.75 square degrees, in at least one band (normally R), and 1.00 square degrees in five passbands. The median seeing, as measured in the final stacked images, is 0.97", ranging from 0.75" to 2.0". The median limiting magnitudes (AB system, 2" aperture, 5 sigma detection limit) are U_(AB)=25.65, B_(AB)=25.54, V_(AB)=25.18, R_(AB) = 24.8 and I_(AB)=24.12 mag, consistent with those proposed in the original survey design. The paper describes the observations and data reduction using the EIS Data Reduction System and its associated EIS/MVM library. The quality of the individual images were inspected, bad images discarded and the remaining used to produce final image stacks in each passband, from which sources have been extracted. Finally, the scientific quality of these final images and associated catalogs was assessed qualitatively by visual inspection and quantitatively by comparison of statistical measures derived from these data with those of other authors as well as model predictions, and from direct comparison with the results obtained from the reduction of the same dataset using an independent (hands-on) software system. Finally to illustrate one application of this survey, the results of a preliminary effort to identify sub-mJy radio sources are reported. To the limiting magnitude reached in the R and I passbands the success rate ranges from 66 to 81% (depending on the fields). These data are publicly available at CDS.Comment: 24 pages, 26 figures. Accepted for pubblication in A&

The Development of Citizen Oriented Informatics

We define the concept of citizen-oriented computer application. Quality characteristics are set for computer applications developed in the conditions of citizen-oriented computing and outline the development cycle for these applications. It defines the conditions of existence for citizen-oriented applications. Average and long-term strategies are elaborated.Distributed Applications, Metrics, Citizen-Orientation, Strategies

Performance evaluation of consumer decision support systems

Consumer decision support systems (CDSSs) help online users make purchasing decisions in e-commerce Web sites. To more effectively compare the usefulness of the various functionalities and interface features of such systems, we have developed a simulation environment for decision tasks of any scale and structure. Furthermore, we have identified three criteria in an evaluation framework for assessing the quality of such CDSSs: users' cognitive effort, preference expression effort, and decision accuracy. A set of experiments carried out in such simulation environments showed that most CDSSs employed in e-commerce Web sites are suboptimal. On the other hand, a hybrid decision strategy based on four existing ones was found to be more effective. The interface improvements based on the new strategy correspond to some of the advanced tools already developed in the research field. This result is therefore consistent with our earlier work on evaluating CDSSs with real users. That is, some advanced tools do produce more accurate decisions while requiring a comparable amount of user effort. However, the simulation environment enables us to efficiently compare more advanced tools among themselves, and indicate further opportunities for functionality and interface improvement

Interaction design guidelines on critiquing-based recommender systems

A critiquing-based recommender system acts like an artificial salesperson. It engages users in a conversational dialog where users can provide feedback in the form of critiques to the sample items that were shown to them. The feedback, in turn, enables the system to refine its understanding of the user's preferences and prediction of what the user truly wants. The system is then able to recommend products that may better stimulate the user's interest in the next interaction cycle. In this paper, we report our extensive investigation of comparing various approaches in devising critiquing opportunities designed in these recommender systems. More specifically, we have investigated two major design elements which are necessary for a critiquing-based recommender system: critiquing coverage—one vs. multiple items that are returned during each recommendation cycle to be critiqued; and critiquing aid—system-suggested critiques (i.e., a set of critique suggestions for users to select) vs. user-initiated critiquing facility (i.e., facilitating users to create critiques on their own). Through a series of three user trials, we have measured how real-users reacted to systems with varied setups of the two elements. In particular, it was found that giving users the choice of critiquing one of multiple items (as opposed to just one) has significantly positive impacts on increasing users' decision accuracy (particularly in the first recommendation cycle) and saving their objective effort (in the later critiquing cycles). As for critiquing aids, the hybrid design with both system-suggested critiques and user-initiated critiquing support exhibits the best performance in inspiring users' decision confidence and increasing their intention to return, in comparison with the uncombined exclusive approaches. Therefore, the results from our studies shed light on the design guidelines for determining the sweetspot balancing user initiative and system support in the development of an effective and user-centric critiquing-based recommender syste