Search results for "Information Retrieval"
showing 10 items of 924 documents
Cross-Domain Recommendations with Overlapping Items
2016
In recent years, there has been an increasing interest in cross-domain recommender systems. However, most existing works focus on the situation when only users or users and items overlap in different domains. In this paper, we investigate whether the source domain can boost the recommendation performance in the target domain when only items overlap. Due to the lack of publicly available datasets, we collect a dataset from two domains related to music, involving both the users’ rating scores and the description of the items. We then conduct experiments using collaborative filtering and content-based filtering approaches for validation purpose. According to our experimental results, the sourc…
User session level diverse reranking of search results
2018
Most Web search diversity approaches can be categorized as Document Level Diversification (DocLD), Topic Level Diversification (TopicLD) or Term Level Diversification (TermLD). DocLD selects the relevant documents with minimal content overlap to each other. It does not take the coverage of query subtopics into account. TopicLD solves this by modeling query subtopics explicitly. However, the automatic mining of query subtopics is difficult. TermLD tries to cover as many query topic terms as possible, which reduces the task of finding a query's subtopics into finding a set of representative topic terms. In this paper, we propose a novel User Session Level Diversification (UserLD) approach bas…
Guidelines for improving the contextual relevance of field surveys: the case of information security policy violations
2014
The information systems (IS) field continues to debate the relative importance of rigor and relevance in its research. While the pursuit of rigor in research is important, we argue that further effort is needed to improve practical relevance, not only in terms of topics, but also by ensuring contextual relevance. While content validity is often performed rigorously, validated survey instruments may still lack contextual relevance and be out of touch with practice. We argue that IS behavioral research can improve its practical relevance without loss of rigor by carefully addressing a number of contextual issues in instrumentation design. In this opinion article, we outline five guidelines – …
Flexible entity search on surfaces
2016
Surface computing allows flexible search interaction where users can manipulate the representation of entities recommended for them to create new queries or augment existing queries by taking advantage of increased screen estate and almost physical tactile interaction. We demonstrate a search system based on 1) Direct Manipulation of Entity Representation on Surfaces and 2) Entity Recommendation and Document Retrieval. Entities are modeled as a knowledge-graph and the relevances of entities are computed using the graph structure. Users can manipulate the representation of entities via spatial grouping and assigning preferences on entities. Our contribution can help to design effective infor…
A two-step, user-centered approach to personalized tourist recommendations
2017
Geo-localized, mobile applications can simplify a tourist visit, making the relevant Point of Interests more easily and promptly discernible to users. At the same time, such solutions must avoid creating unfitting or rigid user profiles that impoverish the users' options instead of refining them. Currently, user profiles in recommender systems rely on dimensions whose relevance to the user is more often presumed than empirically defined. To avoid this drawback, we build our recommendation system in a two-step process, where profile parameters are evaluated preliminarily and separately from the recommendations themselves. We describe this two-step evaluation process including an initial surv…
Social Collaborative Viewpoint Regression with Explainable Recommendations
2017
A recommendation is called explainable if it not only predicts a numerical rating for an item, but also generates explanations for users' preferences. Most existing methods for explainable recommendation apply topic models to analyze user reviews to provide descriptions along with the recommendations they produce. So far, such methods have neglected user opinions and influences from social relations as a source of information for recommendations, even though these are known to improve the rating prediction. In this paper, we propose a latent variable model, called social collaborative viewpoint regression (sCVR), for predicting item ratings based on user opinions and social relations. To th…
Recommending Serendipitous Items using Transfer Learning
2018
Most recommender algorithms are designed to suggest relevant items, but suggesting these items does not always result in user satisfaction. Therefore, the efforts in recommender systems recently shifted towards serendipity, but generating serendipitous recommendations is difficult due to the lack of training data. To the best of our knowledge, there are many large datasets containing relevance scores (relevance oriented) and only one publicly available dataset containing a relatively small number of serendipity scores (serendipity oriented). This limits the learning capabilities of serendipity oriented algorithms. Therefore, in the absence of any known deep learning algorithms for recommend…
On Temporal Aspects in Cross-Cultural e-Collaboration Between Finland and Japan Research Teams
2018
Time is an essential dimension in cross-cultural e-collaboration among research project teams. Understanding temporal aspects and project dynamics in cross-cultural research e-collaboration and related processes can improve team members' skills in cross-cultural communication and increase their cultural competence. The present case cultures are Finnish and Japanese, and the case universities are the University of Jyväskylä (Finland) and Keio University (Japan). Three issues are addressed in this article. First, cultural dimensions and time models in the cross-cultural e-collaboration context are discussed. Second, temporal aspects related to e-collaboration activities are introduced. Third,…
Application of the Information Bottleneck method to discover user profiles in a Web store
2018
The paper deals with the problem of discovering groups of Web users with similar behavioral patterns on an e-commerce site. We introduce a novel approach to the unsupervised classification of user sessions, based on session attributes related to the user click-stream behavior, to gain insight into characteristics of various user profiles. The approach uses the agglomerative Information Bottleneck (IB) algorithm. Based on log data for a real online store, efficiency of the approach in terms of its ability to differentiate between buying and non-buying sessions was validated, indicating some possible practical applications of the our method. Experiments performed for a number of session sampl…
Contrasts in fitness, motor competence and physical activity among children involved in single or multiple sports
2021
Abstract Study aim: While there is wide debate around specialization in one sport, there is a lack of information about fitness levels and motor competence of children participating in single or multiple sports. Material and methods: The study involved 358 fifth-grade children who participated in a set of health-related fitness and motor competence tests over two consecutive years. A subsample of children (n = 109) wore an accelerometer for seven consecutive days. The independent samples t-test and ANCOVA were used to compare differences between single and multi-sport participants in study variables and changes between baseline and follow-up. Results: Multi-sport participants performed bett…