Query Recommendations for OLAP Discovery-Driven Analysis

Recommending database queries is an emerging and promising field of research and is of particular interest in the domain of OLAP systems, where the user is left with the tedious process of navigating large datacubes. In this paper, the authors present a framework for a recommender system for OLAP users that leverages former users’ investigations to enhance discovery-driven analysis. This framework recommends the discoveries detected in former sessions that investigated the same unexpected data as the current session. This task is accomplished by (1) analysing the query log to discover pairs of cells at various levels of detail for which the measure values differ significantly, and (2) analysing a current query to detect if a particular pair of cells for which the measure values differ significantly can be related to what is discovered in the log. This framework is implemented in a system that uses the open source Mondrian server and recommends MDX queries. Preliminary experiments were conducted to assess the quality of the recommendations in terms of precision and recall, as well as the efficiency of their on-line computation.

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Towards Collaborative Multidimensional Query Recommendation with Triadic Association Rules

International Journal of Decision Support System Technology ◽

10.4018/ijdsst.2015070102 ◽

2015 ◽

Vol 7 (3) ◽

pp. 17-35 ◽

Cited By ~ 1

Author(s):

Sid Ali Selmane ◽

Omar Boussaid ◽

Fadila Bentayeb

Keyword(s):

Association Rules ◽

End Users ◽

New Approach ◽

Query Log ◽

Log Files ◽

Query Logs ◽

On Line ◽

Synthetic Datasets ◽

Triadic Context

This paper describes a new personalization process for decisional queries through a new approach based on triadic association rules mining. This process exploits the decision query log files of end users and follows these five steps: (1) generation of a triadic context from the multidimensional query logs of OLAP1 query analysis server; (2) mapping the triadic context into the dyadic one; (3) computation of (conventional) dyadic association rules; (4) generation of triadic association rules through a factorization process of dyadic ones and convey a richer semantics. The aim of the personalization approach which is based on triadic rules is to recommend new decision queries to OLAP end users sharing some common properties. This paper aims at helping this class of users by recommending them personalized OLAP queries that they might use in their future OLAP sessions. To validate the approach, the authors developed a software prototype called P-TRIAR (Personalization based on TRIadic Association Rules) which extracts two types of triadic association rules from decision query log files. The first type of triadic rules will serve to the recommending queries by taking the collaborative aspect of OLAP users into account. The second type of triadic rules will enrich user queries. Preliminary experiments were conducted on both real and synthetic datasets to assess the quality of the recommendations in term of precision and recall measures, as well as the performance of their on-line computation.

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On-Line Discussion and Public Deliberation

Human Affairs ◽

10.2478/v10023-010-0007-y ◽

2010 ◽

Vol 20 (1) ◽

Author(s):

Dušan Ondrušek

Keyword(s):

Open Source ◽

Collective Intelligence ◽

Public Deliberation ◽

On Line ◽

The Difference

On-Line Discussion and Public DeliberationThis paper surveys how the principles of the development of collective intelligence in on-line discussion and the consequences of the open source movement can influence the shape and recommended format of public deliberation processes. It raises the question of the conditions and factors which explain the difference in the quality of discussion results when technological issues are discussed and when values are discussed. It also raises the question of the importance of formats and types of facilitation which allow for deliberation to be structured towards achieving better productivity and the more effective participation of discussion participants.

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Automatic buffer capacity based sensor for effluent quality monitoring

Water Science & Technology ◽

10.2166/wst.1996.0008 ◽

1996 ◽

Vol 33 (1) ◽

pp. 81-87

Author(s):

L. Van Vooren ◽

P. Willems ◽

J. P. Ottoy ◽

G. C. Vansteenkiste ◽

W. Verstraete

Keyword(s):

Wastewater Treatment ◽

Buffer Capacity ◽

Wastewater Treatment Plants ◽

Data Interpretation ◽

Full Scale ◽

Quality Monitoring ◽

Effluent Quality ◽

Capacity Curves ◽

On Line

The use of an automatic on-line titration unit for monitoring the effluent quality of wastewater plants is presented. Buffer capacity curves of different effluent types were studied and validation results are presented for both domestic and industrial full-scale wastewater treatment plants. Ammonium and ortho-phosphate monitoring of the effluent were established by using a simple titration device, connected to a data-interpretation unit. The use of this sensor as the activator of an effluent quality proportional sampler is discussed.

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Audit Reviewers' Judgments in Multiple Client Audit Environments

Behavioral Research in Accounting ◽

10.2308/bria-51788 ◽

2017 ◽

Vol 29 (2) ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Sudip Bhattacharjee ◽

Mario J. Maletta ◽

Kimberly K. Moreno

Keyword(s):

Audit Quality ◽

Internal Audit ◽

Contrast Effects ◽

Comparative Information ◽

A Current

ABSTRACT This study replicates Bhattacharjee, Maletta, and Moreno (2007), who find that audit preparers are susceptible to contrast effects in a multi-client environment. We demonstrate that auditors in the role of reviewers are also susceptible to contrast effects from a prior client. Audit reviewers' assessments of internal audit quality of a current client were significantly affected by the quality of the internal audit group of a client they previously reviewed. Specifically, when auditors first reviewed a client with a weak internal audit group they assessed the subsequent moderate internal audit group as being of higher quality than when they first reviewed a prior client with a strong internal audit group or did not review a prior client. Reviewers' documentation of evidence was also influenced by comparative information from the prior client. These results corroborate the key findings of Bhattacharjee et al. (2007) and confirm audit reviewers' susceptibility to contrast effects.

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Change to the Demands Made of the Teaching Profession and the Ambiguity of New Concepts

Lifelong Learning ◽

10.11118/lifele201202017 ◽

2012 ◽

Vol 2 (1) ◽

pp. 7-18

Author(s):

Jana Kohnová

Keyword(s):

Teaching Profession ◽

Further Education ◽

Career Progression ◽

Quality Of Education ◽

Ministry Of Education ◽

The Czech Republic ◽

New Concepts ◽

Educational Programmes ◽

A Current

This paper is concerned with concepts such as quality of education, evaluation of the standard of the work of the teacher and comparison of educational results. It points to the importance of standards and the difficulties involved in their implementation. It also discusses the concept of competence and its relevance to framework educational programmes and the further education of teachers. The paper also focuses on a number of trends in education that are less widely discussed: instability — permanent change, reduction of education, emphasis on topicality and practical applicability, underestimation of the system, etc. The final part of the paper presents a current project from the Ministry of Education, Youth and Sport of the Czech Republic — a proposal for career progression.

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A standardized framework for testing the performance of sleep-tracking technology: step-by-step guidelines and open-source code

SLEEP ◽

10.1093/sleep/zsaa170 ◽

2020 ◽

Author(s):

Luca Menghini ◽

Nicola Cellini ◽

Aimee Goldstone ◽

Fiona C Baker ◽

Massimiliano de Zambotti

Keyword(s):

Open Source ◽

Validation Studies ◽

Large Scale ◽

Analytical Framework ◽

Clinical Settings ◽

Large Scale Data ◽

Fast Pace ◽

Epoch Analysis ◽

Tracking Devices

Abstract Sleep-tracking devices, particularly within the consumer sleep technology (CST) space, are increasingly used in both research and clinical settings, providing new opportunities for large-scale data collection in highly ecological conditions. Due to the fast pace of the CST industry combined with the lack of a standardized framework to evaluate the performance of sleep trackers, their accuracy and reliability in measuring sleep remains largely unknown. Here, we provide a step-by-step analytical framework for evaluating the performance of sleep trackers (including standard actigraphy), as compared with gold-standard polysomnography (PSG) or other reference methods. The analytical guidelines are based on recent recommendations for evaluating and using CST from our group and others (de Zambotti and colleagues; Depner and colleagues), and include raw data organization as well as critical analytical procedures, including discrepancy analysis, Bland–Altman plots, and epoch-by-epoch analysis. Analytical steps are accompanied by open-source R functions (depicted at https://sri-human-sleep.github.io/sleep-trackers-performance/AnalyticalPipeline_v1.0.0.html). In addition, an empirical sample dataset is used to describe and discuss the main outcomes of the proposed pipeline. The guidelines and the accompanying functions are aimed at standardizing the testing of CSTs performance, to not only increase the replicability of validation studies, but also to provide ready-to-use tools to researchers and clinicians. All in all, this work can help to increase the efficiency, interpretation, and quality of validation studies, and to improve the informed adoption of CST in research and clinical settings.

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An interpretable mechanism for personalized recommendation based on cross feature

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-202308 ◽

2021 ◽

pp. 1-12

Author(s):

Lv YE ◽

Yue Yang ◽

Jian-Xu Zeng

Keyword(s):

Recommender System ◽

Online Shopping ◽

Side Information ◽

Attention Mechanism ◽

Personalized Recommendation ◽

Model Based ◽

Embedded Model ◽

Feature Attention ◽

Match Score

The existing recommender system provides personalized recommendation service for users in online shopping, entertainment, and other activities. In order to improve the probability of users accepting the system’s recommendation service, compared with the traditional recommender system, the interpretable recommender system will give the recommendation reasons and results at the same time. In this paper, an interpretable recommendation model based on XGBoost tree is proposed to obtain comprehensible and effective cross features from side information. The results are input into the embedded model based on attention mechanism to capture the invisible interaction among user IDs, item IDs and cross features. The captured interactions are used to predict the match score between the user and the recommended item. Cross-feature attention score is used to generate different recommendation reasons for different user-items.Experimental results show that the proposed algorithm can guarantee the quality of recommendation. The transparency and readability of the recommendation process has been improved by providing reference reasons. This method can help users better understand the recommendation behavior of the system and has certain enlightenment to help the recommender system become more personalized and intelligent.

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Internal Quality Evolution of Open-Source Software Systems

Applied Sciences ◽

10.3390/app11125690 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5690

Author(s):

Mamdouh Alenezi

Keyword(s):

Open Source ◽

Open Source Software ◽

Software Evolution ◽

Quality Metrics ◽

Internal Quality ◽

Software Systems ◽

Software Metric ◽

Significant Difference ◽

The Relationship

The evolution of software is necessary for the success of software systems. Studying the evolution of software and understanding it is a vocal topic of study in software engineering. One of the primary concepts of software evolution is that the internal quality of a software system declines when it evolves. In this paper, the method of evolution of the internal quality of object-oriented open-source software systems has been examined by applying a software metric approach. More specifically, we analyze how software systems evolve over versions regarding size and the relationship between size and different internal quality metrics. The results and observations of this research include: (i) there is a significant difference between different systems concerning the LOC variable (ii) there is a significant correlation between all pairwise comparisons of internal quality metrics, and (iii) the effect of complexity and inheritance on the LOC was positive and significant, while the effect of Coupling and Cohesion was not significant.

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