Communications of the ACM (CACM for short, not the best sounding acronym around) is the ACM’s flagship magazine. Started in 1957, CACM is handy for keeping up to date on current research being carried out across all topics of computer science and realworld applications. CACM has had an illustrious past with many influential pieces of work and debates started within its pages. These include Hoare’s presentation of the Quicksort algorithm; Rivest, Shamir and Adleman’s description of the first publickey cryptosystem RSA; and Dijkstra’s famous letter against the use of GOTO. In addition to the print edition, which is released monthly, there is a fantastic website (http://cacm.acm. org/) that showcases not only the most recent edition but all previous CACM articles as well, readable online as well as downloadable as a PDF. In addition, the website lets you browse for articles by subject, a handy feature if you want to focus on a particular topic. CACM is really essential reading. Pretty much guaranteed to contain content that is interesting to anyone, it keeps tabs on the latest in computer science. It is a valuable asset for us students, who tend to delve deep into a particular area of CS and forget everything that is happening around us. — Daniel Gooch U ndergraduate research is like a box of chocolates: You never know what kind of project you will get. That being said, there are still a few things you should know to get the most out of the experience.

Communications of the ACM

With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems. A key requirement for the success and adoption of such systems is that users must trust system choices or even fully automated decisions. To achieve this, explanation facilities have been widely investigated as a means of establishing trust in these systems since the early years of expert systems. With today's increasingly sophisticated machine learning algorithms, new challenges in the context of explanations, accountability, and trust towards such systems constantly arise. In this work, we systematically review the literature on explanations in advice-giving systems. This is a family of systems that includes recommender systems, which is one of the most successful classes of advice-giving software in practice. We investigate the purposes of explanations as well as how they are generated, presented to users, and evaluated. As a result, we derive a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems. The taxonomy includes a variety of different facets, such as explanation objective, responsiveness, content and presentation. Moreover, we identified several challenges that remain unaddressed so far, for example related to fine-grained issues associated with the presentation of explanations and how explanation facilities are evaluated.

A systematic review and taxonomy of explanations in decision support and recommender systems

Thank you for reading information systems development methodologies techniques and tools. As you may know, people have search numerous times for their favorite books like this information systems development methodologies techniques and tools, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious bugs inside their desktop computer.

Information Systems Development Methodologies Techniques And Tools

With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems. A key requirement for the success and adoption of such systems is that users must trust system choices or even fully automated decisions. To achieve this, explanation facilities have been widely investigated as a means of establishing trust in these systems since the early years of expert systems. With today’s increasingly sophisticated machine learning algorithms, new challenges in the context of explanations, accountability, and trust towards such systems constantly arise. In this work, we systematically review the literature on explanations in advice-giving systems. This is a family of systems that includes recommender systems, which is one of the most successful classes of advice-giving software in practice. We investigate the purposes of explanations as well as how they are generated, presented to users, and evaluated. As a result, we derive a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems. The taxonomy includes a variety of different facets, such as explanation objective, responsiveness, content and presentation. Moreover, we identified several challenges that remain unaddressed so far, for example related to fine-grained issues associated with the presentation of explanations and how explanation facilities are evaluated.

Interactive technologies have changed - and continue to change - our world. We are living in an era of transformation driven by the Internet, hand-held computing, digital photography, interactive entertainment, and wireless communication technologies. But such transformations are nothing new. Adoption of many technologies has transformed our work, play, communication, and thought. It has also transformed our research and practice in the HCI community.CHI 2002 explores transforming technologies, looking back to the past and forward to the future. First, by reflecting on past (and current) technologies, we seek a better understanding of questions like: Why do some technologies succeed where others fail? How have economic and work conditions and leisure been changed? What roles have technologists, entrepreneurs, legislators, lawyers, and citizens played? We examine these issues especially as they relate to HCI, a young field that will celebrate its 20th anniversary at CHI 2002.Second, we look forward, examining emerging technologies and involving us all in shaping their progress. Profound HCI issues are raised as computer and communications technologies progress from portable to wearable to implantable, as the power and speed of technology increases and the cost decreases, and as the standard desktop graphical interface is augmented by mobile devices, tangible and mixed reality interfaces. In response, we ask: What role should HCI professionals play in the development and deployment of such profoundly transformative devices and the socio-technical systems surrounding them? How can we ensure usability and a regard for personal privacy? What is the role of the legal and political system can they "keep up" with technology, or do sufficiently compelling technologies simply push them aside.Third, in addition to looking outward, CHI 2002 has looked inward to the practices of our community. We used some new technologies to nudge the CHI conference in the direction of greater interactivity, turning attendees into participants. CHIplace.org, our interactive online forum, enables people to exchange ideas, offer suggestions, and preview conference content. As part of CHIs increasing emphasis on issues of interest to designers and usability practitioners, CHI 2002 features the Practitioners Special Track. Professional and student designers present portfolios of their work, and usability professionals reflect on the experiences they have gained with usability methods in practice. CHI 2002 also is proud to feature a two-day forum, the CHI 2002|AIGA Experience Design Forum. Held in collaboration with the Experience Design Group of AIGA, the American Institute of Graphic Arts, this forum serves as an in-depth, interdisciplinary exploration of issues in design and human-computer interaction.

CHI '02 Extended Abstracts on Human Factors in Computing Systems

Recommender systems provide suggestions for products, services, or information that match users’ interests and/or needs. However, not all recommendations persuade users to select or use the recommended item. The Elaboration Likelihood Model (ELM) suggests that individuals with low motivation or ability to process the information provided with a recommended item could eventually get persuaded to select/use the item if appropriate peripheral cues enrich the recommendation. The purpose of this research is to investigate the persuasive effect of certain influence strategies and the role of personality in the acceptance of recommendations. In the present study, a movie Recommender System was developed in order to empirically investigate the aforementioned questions applying certain persuasive strategies in the form of textual messages alongside the recommended item. The statistical method of Fuzzy-Set Qualitative Comparative Analysis (fsQCA) was used for data analysis and the results revealed that motivating messages do change users’ acceptance of the recommender item but not unconditionally since user’s personality differentiates the effect of the persuasive strategies.

/pdf/investigating-the-role-of-personality-traits-and-influence-10lkse5z70.pdf

Investigating the Role of Personality Traits and Influence Strategies on the Persuasive Effect of Personalized Recommendations.

The paper examines the persuasive effect of explanations on the intention of users to use recommended items. For the needs of the present study, a movie Recommender System was built so as to elicit participants' preferences about movies and then a movie is recommended in order to investigate the effect of the application of Cialdini's Influence Principle(s), implemented as recommendation explanations, on the users' intention to watch the movie. Surprisingly, the experimental results of the study suggest that if a Recommender System provides persuasive explanations for a product/service that is close to a user's preferences and tastes then it changes his/her behaviour.

Investigating the Effectiveness of Persuasion Strategies on Recommender Systems

Recommender Systems have obvious influence in environments where data size exceeds the capabilities of any user to fully explore the available choices in the store (physical or on-line). Many algorithms and techniques have been used to help recommending useful and interesting items to users. If the user is unidentified, the process is even harder as there are no historical or other data to use as input. Association rules is a popular technique used for many purposes in Recommender Systems such as for building more robust systems, improving quality of recommendations; and even addressing fundamental limitations of recommender systems and, generally, large datasets, e.g. sparsity and cold start. At the same time, efforts have been made to fully understand if and how differently customers are behaving in an online and in a physical environment.This work tries to combine the two efforts. We use association rules to provide recommendations to customers, as well as understand who the customer is, what her needs are and what is her mentality when entering a physical store or the corresponding e-shop. To fulfill our goal, we used descriptive statistics along with Association Rules analysis of the POS transactional data on basket data level and historical data level.

Garment Recommendations for Online and Offline Consumers

Recommender Systems have been traditionally utilized in online environments to personalize product and service offerings and can contribute towards the persuasion of a user to select or consume the recommended items. The present study examines the aforementioned systems in ubiquitous environments and focuses on the persuasive role of customer’s motivational conditions to consume a product as well as factors affecting consumers’ acceptance in recommendation systems. One of the main insights of the study demonstrates that when a consumer has low motivation to purchase an item then (s)he has the intention to purchase more garments than in the case of high motivation to purchase a particular garment. Furthermore, the present study examines and evaluates the effect of novel and serendipitous recommendations on the above motivational conditions. The results revealed that when a consumer has either high or low motivation to purchase a garment, (s)he gets persuaded by serendipitous garment recommendations while the provision of novel recommendations does not affect the acceptance of recommendations in any of the two motivational conditions.

/pdf/persuasive-recommendations-in-ubiquitous-environments-ot1goehci6.pdf

Persuasive Recommendations in Ubiquitous Environments.

Recommender Systems are traditionally been used in online environments. The present study focuses on factors affecting consumers’ acceptance in recommendation systems that will be used in traditional stores. For this purpose, we have developed a garment recommendation system applying and evaluating the aforementioned factors through an experiment. The main insights of the study indicate that consumers’ personality affect consumers’ preferences and garments’ style. Additionally, when a consumer has high motivation to purchase a particular garment (s)he does not waste his/her time for looking around other types of garments. This means that if a garment provider wants to increase cross selling then he has to recommend products that are close to that event such as accessories.

Factors Affecting Recommendations' Acceptance in Off-Line Environment

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