A graphical shopping interface bases on product attributes

Most recommender systems present recommended products in lists to the user. By doing so, much information is lost about the mutual similarity between recommended products. We propose to represent the mutual similarities of the recommended products in a two dimensional space, where similar products are located close to each other and dissimilar products far apart. As a dissimilarity measure we use an adaptation of Gower's similarity coefficient based on the attributes of a product. Two recommender systems are developed that use this approach. The first, the graphical recommender system, uses a description given by the user in terms of product attributes of an ideal product. The second system, the graphical shopping interface, allows the user to navigate towards the product he wants. We show a prototype application of both systems to MP3-players

Building an Archive with Saada

Saada transforms a set of heterogeneous FITS files or VOTables of various categories (images, tables, spectra ...) in a database without writing code. Databases created with Saada come with a rich Web interface and an Application Programming Interface (API). They support the four most common VO services. Such databases can mix various categories of data in multiple collections. They allow a direct access to the original data while providing a homogenous view thanks to an internal data model compatible with the characterization axis defined by the VO. The data collections can be bound to each other with persistent links making relevant browsing paths and allowing data-mining oriented queries.Comment: 18 pages, 5 figures Special VO issu

Map Based Visualization of Product Catalogs

Traditionally, recommender systems present recommendations in lists to the user. In content- and knowledge-based recommendation systems these list are often sorted on some notion of similarity with a query, ideal product specification, or sample product. However, a lot of information is lost in this way, since two even similar products can differ from the query on a completely different set of product characteristics. When using a two dimensional, that is, a map-based, representation of the recommendations, it is possible to retain this information. In the map we can then position recommendations that are similar to each other in the same area of the map. Both in science and industry an increasing number of two dimensional graphical interfaces have been introduced over the last years. However, some of them lack a sound scientific foundation, while other approaches are not applicable in a recommendation setting. In our chapter, we will describe a framework, which has a solid scientific foundation (using state-of-the-art statistical models) and is specifically designed to work with e-commerce product catalogs. Basis of the framework is the Product Catalog Map interface based on multidimensional scaling. Also, we show another type of interface based on nonlinear principal components analysis, which provides an easy way in constraining the space based on specific characteristic values. Then, we discuss some advanced issues. Firstly, we discuss how the product catalog interface can be adapted to better fit the users' notion of importance of attributes using click stream analysis. Secondly, we show an user interface that combines recommendation by proposing with the map based approach. Finally, we show how these methods can be applied to a real e-commerce product catalog of MP3-players

Choosing Attribute Weights for Item Dissimilarity using Clikstream Data with an Application to a Product Catalog Map

In content- and knowledge-based recommender systems often a measure of (dis)similarity between items is used. Frequently, this measure is based on the attributes of the items. However, which attributes are important for the users of the system remains an important question to answer. In this paper, we present an approach to determine attribute weights in a dissimilarity measure using clickstream data of an e-commerce website. Counted is how many times products are sold and based on this a Poisson regression model is estimated. Estimates of this model are then used to determine the attribute weights in the dissimilarity measure. We show an application of this approach on a product catalog of MP3 players provided by Compare Group, owner of the Dutch price comparison site http://www.vergelijk.nl, and show how the dissimilarity measure can be used to improve 2D product catalog visualizations.dissimilarity measure;attribute weights;clickstream data;comparison

A modularized electronic payment system for agent-based e-commerce

With the explosive growth of the Internet, electronic-commerce (e-commerce) is an increasingly important segment of commercial activities on the web. The Secure Agent Fabrication, Evolution & Roaming (SAFER) architecture was proposed to further facilitate e-commerce using agent technology. In this paper, the electronic payment aspect of SAFER will be explored. The Secure Electronic Transaction (SET) protocol and E-Cash were selected as the bases for the electronic payment system implementation. The various modules of the payment system and how they interface with each other are shown. An extensible implementation done using JavaTM will also be elaborated. This application incorporates agent roaming functionality and the ability to conduct e-commerce transactions and carry out intelligent e-payment procedures

Business intelligence as the support of decision-making processes in e-commerce systems environment

The present state of world economy urges managers to look for new methods, which can help to start the economic growth. To achieve this goal, managers use standard as well as new procedures. The fundamental prerequisite of the efficient decision-making processes are actual and right information. Managers need to monitor past information and current actual information to generate trends of future development based on it. Managers always should define strictly what do they want to know, how do they want to see it and for what purpose do they want to use it. Only in this case they can get right information applicable to efficient decision-making. Generally, managers´ decisions should lead to make the customers´ decision-making process easier. More frequently than ever, companies use e-commerce systems for the support of their business activities. In connection with the present state and future development, cross-border online shopping growth can be expected. To support this, companies will need much better systems providing the managers adequate and sufficient information. This type of information, which is usually multidimensional, can be provided by the Business Intelligence (BI) technologies. Besides special BI systems, some of BI technologies are obtained in quite a few of ERP (Enterprise Resource Planning) systems. One of the crucial questions is whether should companies and firms buy or develop special BI software, or whether they can use BI tools contained in some ERP systems. In respect of this, there is a question if the modern ERP systems can provide the managers sufficient possibilities relating to ad-hoc reporting, static and dynamic reports and OLAP analyses. A one of the main goals of this article is to show and verify Business Intelligence tools of Microsoft Dynamics NAV for the support of decision-making in terms of the cross-border online purchasing. Pursuant to above-mentioned, in this article authors deal with problems relating to managers´ decision-making, customers´ decision-making and a support of its using the BI tools contained in ERP system Microsoft Dynamics NAV. A great deal of this article is aimed at area of multidimensional data which are the source data of e-commerce systems.Business Intelligence, decision-making, e-commerce system, cross-border online purchasing, multi-dimensional data, reporting, data visualization

Analysing the Role of Interactivity in User Experience

An experimental investigation into the role of interaction in user experience (UX) with a controlled manipulation of interactivity features (e.g. avatars, interactive video) in a university information website is reported. The more interactive version had better affect and hedonic ratings, even though its perceived usability was worse. Analysis of qualitative data showed users were attracted to the interactive features, although they complained about poor usability. The results of the experiments are discussed to consider the role of interactivity in user experience and the differences between users’ quantitative judgements of UX and their comments on interactive features which reveal different perspectives

Smart Brokering for Household Items

Households will normally feel very annoyed when they want to buy a product but the budget is limited. Thus, a wise consumer will carry out product price survey before purchasing so that he or she is able to buy the desired product within the required budget. This project proposes the development of a Smart Brokering System for product price survey activity so that to ease consumers in their daily routine in selecting the household products. In this project, a price comparison system for household products will be developed to display all possible product prices from several grocery stores based on the budget preferences set by the consumers. In particular, the proposed system will be developed by using a full-text search library, which the data is already been populated in the database to implement the data retrieval process. This system is written in C# and ASP .Net. Apart from that, system testing is carried out by the author to test the algorithm so that the functions are working smoothly and perfectly. Acceptance tests has been done by the potential consumers to make sure the end product meet the users’ requirement. As a result, the expected outcome of this research is to improve the easiness of shopping and the efficiency of price surveying activity by the consumer

Linking consumer trust perception in constructing an e-commerce trust model

Trust issues is still considered as a main obstacle in the implementation of eCommerce Due to the increasing numbers of cyber crimes committed today, consumers are faced with doubt to engage in online shopping. As a safety precaution, consumers will take certain measures to protect their information by evaluating and assessing these websites trustworthiness before an actual purchase occurs. This paper describes a model that examines the elements related to online consumer behavior and to investigate this behavior towards building and increasing trust. The applicability of the model was tested in attempt to view consumers' acceptance towards the model and its component. The fmdings indicate the respondents are aware of the trust issue surrounding e-Commerce implementation as they accept and agreed with the model and its components