1,721,171 research outputs found
Proceedings of the 22nd International Configuration Workshop
Full text linkThe 2020 Workshop on Configuration continues the series of successful workshops organized within IJCAI, AAAI, and ECAI since 1999. Starting from 2013, the workshop was held independently from major conferences. Even in this 22nd edition, beside researchers from a variety of different fields, it attracted a significant number of industrial participants from major configurator vendors as well as from end-users. The 2020 Workshop on Configuration is a standalone two-day event. It was planned to takes place in Vicenza, Italy at the Department of Management and Engineering of Padova University. Due to COVID19 pandemic, it has been moved online. A total of 18 papers were selected for presentation on the Configuration Workshop. All papers underwent to full paper blind review with a minimum of two independent reviewers per paper. All papers have been substantially changed to comply with the reviewers’ observations. The themes of the technical sessions are knowledge representation & reasoning, peculiar technologies for configuration (machine learning, conversational agents (chatboats and voiceboats), social software, Microsoft excel), configuration of products in use (reconfiguration, adaptation, renovation, maintenance, repair), business applications with a special focus on the provision of empirical data to depict the state of the art on configuration practices
Product configuration activities in SMEs and their digitalization: Preliminary results of a survey study
Full text linkThe presence of customization in manufacturing small and medium enterprises (SMEs) is widely known, as is the competitive pressure that even they have to deal with. We also know that there are examples of successful applications of product configurators in SMEs, even in quite small ones. However, we do not know the extent of the presence, in SMEs, of the various product configuration activities or the intensity of their digitalization. The present study offers some preliminary results of research aimed at gaining further insights into product configuration activities in SMEs. Specifically, the present study provides preliminary empirical results gathered in a sample of 18 Italian SMEs. It emerges that configuration activities are frequently present in manufacturing SMEs and that there is a high potential for their digitalization
Product visualization in configurators: Laying the foundations for a comparative description
No full textVisualization plays a critical role in the purchasing process, particularly for customized products, as it improves customer engagement and decision-making. Despite the importance of product configurators in presenting customized products, there is limited research on the characteristics of visualization modes that configurators employ. This study aims to address this gap by developing an evaluation framework consisting of 11 descriptive variables: embodiment, presence, interactivity, authenticity, realism, media richness, avatar similarity, functional control, visual control, interaction richness, and vividness. Each variable of the framework is defined and exemplified by practical examples. These variables, derived from the literature on e-commerce and customer experience, offer a structured framework to describe and compare product visualization modes in configurators
IntRS 2014 Interfaces and Human Decision Making for Recommender Systems, Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2014). Foster City, Silicon Valley, USA, October 6, 2014
No full textAs an interactive intelligent system, recommender systems are developed to suggest
items that match users’ preferences. Since the emergence of recommender systems, a large majority of research has focused on objective accuracy criteria and less attention has been paid to how users interact with the system and the efficacy of interface designs
from users’ perspectives. The field has reached a point where it is ready to look beyond algorithms, into users’ interactions, decision making processes and overall experience.
Accordingly, the goals of the workshop are to explore the human aspects of
recommender systems, with a particular focus on the impact of interfaces and interaction design on decision-making and user experiences with recommender systems, and to explore methodologies to evaluate these human aspects of the recommendation process that go beyond traditional automated approaches.
The aim is to bring together researchers and practitioners around the topics of designing and evaluating novel intelligent interfaces for recommender systems in order to:
(1) share research and techniques, including new design technologies and evaluation methodologies
(2) identify next key challenges in the area, and (3) identify emerging topics.
The workshop covers three interrelated themes:
a) user interfaces (e.g. visual interfaces, explanations),
b) interaction, user modeling and decision-making (e.g. decision theories, argumentation, detection and avoidance of biases), and
c) evaluation (e.g. case studies and empirical evaluations).
This workshop aims at creating an interdisciplinary community with a focus on the
interface design issues for recommender systems and promoting collaboration
opportunities between researchers and practitioners.
The workshop consists of a mix of eight presentations of papers in which results of
ongoing research as reported in these proceedings are presented and one invited talk by Julita Vassileva presenting “Visualization and User Control of Recommender Systems”.
The workshop is closed by a final discussion session
Human Decision Making and Recommender Systems
No full textRecommender Systems have already proved to be valuable for coping with the information overload problem
in several application domains. They provide people with suggestions for items which are likely to be
of interest for them; hence, a primary function of recommender systems is to help people make good choices
and decisions. However, most previous research has focused on recommendation techniques and algorithms, and less attention has been devoted to the decision making processes adopted by the users and possibly supported by the system. There is still a gap between the importance that the community gives to the assessment of recommendation algorithms and the current range of ongoing research activities concerning
human decision making. Different decision-psychological phenomena can influence the decision making of users of recommender systems, and research along these lines is becoming increasingly important and popular.
This special issue highlights how the coupling of recommendation algorithms with the understanding of human choice and decision making theory has the potential to benefit research and practice on recommender systems and to enable users to achieve a good balance between decision accuracy and decision effort
Decisions@RecSys 2013, Human Decision Making in Recommender Systems. Proceedings of the 3rd Workshop on Human Decision Making in Recommender Systems, in conjunction with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 12, 2013
No full textUsers interact with recommender systems to obtain useful information about products or services that may be of interest for them. But, while users are interacting with a recommender system to fulfill a primary task, which is usually the selection of one or more items, they are
facing several other decision problems. For instance, they may be requested to select specific feature values (e.g., camera’s size, zoom) as criteria for a search, or they could have to identify features to be used in a critiquing based recommendation session, or they may need to select a
repair proposal for inconsistent user preferences when interacting with a recommender. In all these scenarios, and in many others, users of recommender systems are facing decision tasks.
The complexity of decision tasks, limited cognitive resources of users, and the tendency to keep the overall decision effort as low as possible is modeled by theories that conjecture “bounded rationality”, i.e., users are exploiting decision heuristics rather than trying to take an optimal.
Furthermore, preferences of users will likely change throughout a recommendation session, i.e., preferences are constructed in a specific decision context and users may not fully know their preferences beforehand. Within the scope of a decision process, preferences are strongly influenced by the goals of the customer, existing cognitive constraints, and the personal
experience of the customer. Due to the fact that users do not have stable preferences, the interaction mechanisms provided by a recommender system and the information shown to a user can have an enormous impact on the outcome of a decision process.
Theories from decision psychology and cognitive psychology have already elaborated a number of methodological tools for explaining and predicting the user behavior in these scenarios. The major goal of this workshop is to establish a platform for industry and academia to present and
discuss new ideas and research results that are related to the topic of human decision making in recommender systems. The workshop consists of a mix of six presentations of papers in which results of ongoing research as reported in these proceedings are presented and two invited talks: Bart Knijnenburg presenting “Simplifying privacy decisions: towards interactive and adaptive solutions” and Jill Freyne and Shlomo Berkovsky presenting: “Food
Recommendations: Biases that Underpin Ratings”. The workshop is closed by a final discussion session
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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