Search results for "Data"
showing 10 items of 12992 documents
Anomaly Detection Algorithms for the Sleeping Cell Detection in LTE Networks
2015
The Sleeping Cell problem is a particular type of cell degradation in Long-Term Evolution (LTE) networks. In practice such cell outage leads to the lack of network service and sometimes it can be revealed only after multiple user complains by an operator. In this study a cell becomes sleeping because of a Random Access Channel (RACH) failure, which may happen due to software or hardware problems. For the detection of malfunctioning cells, we introduce a data mining based framework. In its core is the analysis of event sequences reported by a User Equipment (UE) to a serving Base Station (BS). The crucial element of the developed framework is an anomaly detection algorithm. We compare perfor…
User experience targets as design drivers:A case study on the development of a remote crane operator station
2013
In recent years, the notion of user experience, or UX, as an essential aspect to be addressed in the design and development of technologies has been increasingly discussed. In this paper, we present a case study in which we have used UX targets as the main design drivers and focus areas in developing a new remote operator station user interface for container cranes. UX targets describe the experiential qualities to which the product design should aim at. However, taking UX targets into consideration during product design is challenging, because only little is known about how they would be best operationalized to serve the different phases of the design process. Through our case study, we de…
A modelling framework for social media monitoring
2013
This paper describes a hierarchical, three-level modelling framework for monitoring social media. Immediate social reality is modelled through the first level of the models. They represent various virtual communities at social media sites and adhere to the social world models of the sites, i.e., the "site ontologies". The second-level model is a temporal multirelational graph that captures the static and dynamic properties of the first-level models from the perspective of the monitoring site. The third-level model consists of a temporal relational database scheme that models the temporal multirelational graph within the database. The models are specified and instantiated at the monitoring s…
A Generic Architecture for a Social Network Monitoring and Analysis System
2011
This paper describes the architecture and a partial implementation of a system designed for the monitoring and analysis of communities at social media sites. The main contribution of the paper is a novel system architecture that facilitates long-term monitoring of diverse social networks existing and emerging at various social media sites. It consists of three main modules, the crawler, the repository and the analyzer. The first module can be adapted to crawl different sites based on ontology describing the structure of the site. The repository stores the crawled and analyzed persistent data using efficient data structures. It can be implemented using special purpose graph databases and/or …
Twister Tries
2015
Many commonly used data-mining techniques utilized across research fields perform poorly when used for large data sets. Sequential agglomerative hierarchical non-overlapping clustering is one technique for which the algorithms’ scaling properties prohibit clustering of a large amount of items. Besides the unfavorable time complexity of O(n 2 ), these algorithms have a space complexity of O(n 2 ), which can be reduced to O(n) if the time complexity is allowed to rise to O(n 2 log2 n). In this paper, we propose the use of locality-sensitive hashing combined with a novel data structure called twister tries to provide an approximate clustering for average linkage. Our approach requires only lin…
A Hybrid Multigroup Coclustering Recommendation Framework Based on Information Fusion
2015
Collaborative Filtering (CF) is one of the most successful algorithms in recommender systems. However, it suffers from data sparsity and scalability problems. Although many clustering techniques have been incorporated to alleviate these two problems, most of them fail to achieve further significant improvement in recommendation accuracy. First of all, most of them assume each user or item belongs to a single cluster. Since usually users can hold multiple interests and items may belong to multiple categories, it is more reasonable to assume that users and items can join multiple clusters (groups), where each cluster is a subset of like-minded users and items they prefer. Furthermore, most of…
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…
Open Resources as the Educational Basis for a Bachelor-level Project-Based Course
2015
This article presents an innovation-based course concept for project-based learning. In this course, student groups are asked to ideate and implement a software product based on Open Data and Open API releases. By emphasizing studentsâ own product ideation, the course requires and enhances self-directed learning skills and prompts the students to see the unlimited possibilities in becoming and being a practitioner of the computing discipline. Relatedly, the course provides a tool to improve student self-efficacy, as the students, coached through challenges, come to know that they are able to produce software using various open interfaces.
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 – …