Contextual location prediction using spatio-temporal clustering

2016 ◽  
Vol 12 (3) ◽  
pp. 290-309 ◽  
Author(s):  
Djamel Guessoum ◽  
Moeiz Miraoui ◽  
Chakib Tadj
Keyword(s):  
Pervasive Computing ◽  
Spatial Clustering ◽  
Contextual Information ◽  
Real Data ◽  
Temporal Segmentation ◽  
Data Set ◽  
Content Type ◽  
Points Of Interest ◽  
Day Of The Week ◽  
Spatio Temporal

Purpose The prediction of a context, especially of a user’s location, is a fundamental task in the field of pervasive computing. Such predictions open up a new and rich field of proactive adaptation for context-aware applications. This study/paper aims to propose a methodology that predicts a user’s location on the basis of a user’s mobility history. Design/methodology/approach Contextual information is used to find the points of interest that a user visits frequently and to determine the sequence of these visits with the aid of spatial clustering, temporal segmentation and speed filtering. Findings The proposed method was tested with a real data set using several supervised classification algorithms, which yielded very interesting results. Originality/value The method uses contextual information (current position, day of the week, time and speed) that can be acquired easily and accurately with the help of common sensors such as GPS.

scholarly journals The day-of-the-week effect: South African stock market indices

2018 ◽  
Vol 9 (2) ◽  
pp. 197-212 ◽  
Author(s):  
Elda du Toit ◽  
John Henry Hall ◽  
Rudra Prakash Pradhan
Keyword(s):  
South African ◽  
Stock Exchange ◽  
Garch Model ◽  
Statistical Technique ◽  
Data Set ◽  
Content Type ◽  
Johannesburg Stock Exchange ◽  
Time Period ◽  
Day Of The Week ◽  
Micro Level

Purpose The presence of a day-of-the-week effect has been investigated by many researchers over many years, using a variety of financial data and methods. However, differences in methodology between studies could have led to conflicting results. The purpose of this paper is to expand on an existing study to observe whether an analysis of the same data set with some added years and using a different statistical technique provide the same results. Design/methodology/approach The study examines the presence of a day-of-the-week effect on the Johannesburg Stock Exchange (JSE) indices for the period March 1995-2016, using a GARCH model. Findings The findings show that, contrary to the original study, the day-of-the week effect is present in both volatility and return equations. The highest and lowest returns are observed on Monday and Friday, respectively, while volatility is observed on all five days from Monday to Friday. Originality/value This study adds to the existing literature on day-of-the-week effect of JSE indices, where different patterns or, in some cases, no pattern have been noted. Few previous studies on the day-of-the-week effect observed the effect at micro-level for separate industries or made use of a GARCH model. The present study thus expands on the study of Mbululu and Chipeta (2012), by adding four additional observation years and using a different statistical technique, to observe differences that arise from a different time period and statistical technique. The results indicate that a day-of-the-week effect is mostly a function of the statistical technique applied.

Hedonic value and crowdfunding project performance: a propensity score matching-based analysis

2017 ◽  
Vol 9 (2) ◽  
pp. 169-186 ◽  
Author(s):  
Liang Zhao ◽  
Tsvi Vinig
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Real Data ◽  
Project Performance ◽  
Probit Regression ◽  
Data Set ◽  
Content Type ◽  
Hedonic Value ◽  
Utilitarian Value ◽  
The Impact

Purpose In the existing literature on crowdfunding project performance, previous studies have given little attention to the impact of investors’ hedonic value and utilitarian value on project results. In a crowdfunding setting, utilitarian value is somehow hard to satisfy due to information asymmetry and adverse selection problem. Therefore, the projects with more hedonic value can be more attractive for potential investors. Lucky draw is a method to increase consumer hedonic value, and it can influence investors’ behavior as a result. The authors hypothesize that projects with hedonic treatment (lucky draw) may have higher probability to win their campaign than others. The paper aims to discuss these issues. Design/methodology/approach A unique self-extracted two-year Chinese crowdfunding platform real data set has been applied as the analysis sample. The authors first employ propensity score matching methods to control for the endogeneity of hedonic treatment adoption (lucky draw). The authors then run OLS regression and probit regression in order to test the hypotheses. Findings The analysis suggests a significant positive relationship not only between project lottery adoption and project results but also between project lottery adoption and project popularity. Originality/value The results suggest that an often ignored factor – hedonic treatment (lucky draw) – can play an important role in crowdfunding project performance.

Empirical study on the effect of using synthetic attributes on classification algorithms

2017 ◽  
Vol 10 (2) ◽  
pp. 111-129 ◽  
Author(s):  
Ali Hasan Alsaffar
Keyword(s):  
Data Mining ◽  
Empirical Study ◽  
Student Performance ◽  
Software Tool ◽  
Real Data ◽  
Support Vector ◽  
Classification Algorithms ◽  
Past Performance ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to present an empirical study on the effect of two synthetic attributes to popular classification algorithms on data originating from student transcripts. The attributes represent past performance achievements in a course, which are defined as global performance (GP) and local performance (LP). GP of a course is an aggregated performance achieved by all students who have taken this course, and LP of a course is an aggregated performance achieved in the prerequisite courses by the student taking the course. Design/methodology/approach The paper uses Educational Data Mining techniques to predict student performance in courses, where it identifies the relevant attributes that are the most key influencers for predicting the final grade (performance) and reports the effect of the two suggested attributes on the classification algorithms. As a research paradigm, the paper follows Cross-Industry Standard Process for Data Mining using RapidMiner Studio software tool. Six classification algorithms are experimented: C4.5 and CART Decision Trees, Naive Bayes, k-neighboring, rule-based induction and support vector machines. Findings The outcomes of the paper show that the synthetic attributes have positively improved the performance of the classification algorithms, and also they have been highly ranked according to their influence to the target variable. Originality/value This paper proposes two synthetic attributes that are integrated into real data set. The key motivation is to improve the quality of the data and make classification algorithms perform better. The paper also presents empirical results showing the effect of these attributes on selected classification algorithms.

scholarly journals Adaptive Multisensor Acquisition via Spatial Contextual Information for Compressive Spectral Image Classification

2021 ◽  
Author(s):  
Nelson Diaz ◽  
Juan Marcos ◽  
Esteban Vera ◽  
Henry Arguello
Keyword(s):  
Image Classification ◽  
State Of The Art ◽  
Contextual Information ◽  
Real Data ◽  
Experimental Setup ◽  
Spectral Image ◽  
Data Set ◽  
Adaptive Sensing

Results of extensive simulations are shown for two state-of-the-art databases: Pavia University and Indian Pines. Furthermore, an experimental setup that performs the adaptive sensing was built to test the performance of the proposed approach on a real data set.

Semantic network edges: a human-machine approach to represent typed relations in social networks

2015 ◽  
Vol 19 (1) ◽  
pp. 71-81 ◽  
Author(s):  
M. Cristina Pattuelli ◽  
Matthew Miller
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Semantic Network ◽  
Contextual Information ◽  
Open Data ◽  
Entity Recognition ◽  
Semantic Web Technologies ◽  
Data Set ◽  
Content Type ◽  
External Data

Purpose – The purpose of this paper is to describe a novel approach to the development and semantic enhancement of a social network to support the analysis and interpretation of digital oral history data from jazz archives and special collections. Design/methodology/approach – A multi-method approach was applied including automated named entity recognition and extraction to create a social network, and crowdsourcing techniques to semantically enhance the data through the classification of relations and the integration of contextual information. Linked open data standards provided the knowledge representation technique for the data set underlying the network. Findings – The study described here identifies the challenges and opportunities of a combination of a machine and a human-driven approach to the development of social networks from textual documents. The creation, visualization and enrichment of a social network are presented within a real-world scenario. The data set from which the network is based is accessible via an application programming interface and, thus, shareable with the knowledge management community for reuse and mash-ups. Originality/value – This paper presents original methods to address the issue of detecting and representing semantic relationships from text. Another element of novelty is in that it applies semantic web technologies to the construction and enhancement of the network and underlying data set, making the data readable across platforms and linkable with external data sets. This approach has the potential to make social networks dynamic and open to integration with external data sources.

Measures of customers’ perception of car Ijarah financing

2018 ◽  
Vol 9 (1) ◽  
pp. 2-16 ◽  
Author(s):  
Asim Ehsan Wahla ◽  
Hamid Hasan ◽  
M. Ishaq Bhatti
Keyword(s):  
Quality Of Service ◽  
Real Data ◽  
Islamic Banks ◽  
Data Set ◽  
Content Type ◽  
Customer Base ◽  
Finance Industry ◽  
Logit Regression Model ◽  
Practical Implications

Purpose The main aim of this paper is to measure customers’ perception of car Ijarah financing transactions services provided by the Islamic banks and financial institutions in Pakistan. Design/methodology/approach The paper uses two research methodologies: Kruskal–Wallis and Mann–Whitney test (non-parametric) and logit regression model (parametric). Both methods are then applied to a real data set of 300 respondents from various cities of Pakistan in the car Ijarah financing industry. The demographic effects are also investigated to see the perception about the degree of Shari’ah compliance and the quality of service of transaction offered by banks. Findings Main finds of the paper reveal that the customers who used the car Ijarah facility from Islamic banks have positive attitude toward this sort of transaction. In addition, gender, income, marital status affect the perception about the quality of Shari’ah compliance, and the quality of service of transaction issues are very important to selected clients in the industry. Research limitations/implications These findings are limited to the car Ijarah financing industry and may not be applicable in other banking products in Pakistan and elsewhere. Practical implications Based on the results of this study, potential Islamic bank customers may find it helpful choose products or make product decisions conveniently. The findings of the paper also support Islamic banks in improving the Ijarah facility to increase their customer base in the geo-political locality with similar characteristics as Pakistan. Social implications Shari’ah compliance in the Islamic finance industry is a sensitive issue in Pakistan, and hence, car Ijarah’s Shari’ah compliance can affect banks’ reputation and sensitivity. Originality/value The work reported in this paper is original, unpublished and the paper is not submitted elsewhere for publication.

A policy-based middleware for context-aware pervasive computing

2015 ◽  
Vol 11 (1) ◽  
pp. 43-68 ◽  
Author(s):  
Mehdia Ajana El Khaddar ◽  
Mhammed Chraibi ◽  
Hamid Harroud ◽  
Mohammed Boulmalf ◽  
Mohammed Elkoutbi ◽  
...  
Keyword(s):  
Ubiquitous Computing ◽  
Pervasive Computing ◽  
Design Methodology ◽  
Contextual Information ◽  
Context Aware ◽  
Content Type ◽  
Heterogeneous Devices ◽  
Computing Environments ◽  
Physical Spaces ◽  
Ubiquitous Computing Environments

Purpose – This paper aims to demonstrate that a policy-based middleware solution which facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. Ubiquitous computing targets the provision of seamless services and applications by providing an environment that involves a variety of devices having different capabilities. These applications help transforming the physical spaces into computationally active and smart environments. The design of applications in these environments needs to consider the heterogeneous devices, applications preferences and rapidly changing contexts. The applications, therefore, need to be context-aware so that they can adapt to different situations in real-time. Design/methodology/approach – In this paper, we argue that a policy-based middleware solution that facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. The middleware allows applications to track items and acquire contextual information about them easily, reason about this information captured using different logics and then adapt to changing contexts. A key issue in these environments is to allow heterogeneous applications to express their business rules once, and get the preferred data once they are captured by the middleware without any intervention from the application side. Findings – Our middleware tackles this problem by using policies to define the different applications’ rules and preferences. These policies can specify rules about the middleware services to be used, type of data captured, devices used, user roles, context information and any other type of conditions. Originality/value – In this paper, we propose the design of a flexible and performant ubiquitous computing, and context-aware middleware called FlexRFID along with its evaluation results.

Path-based keyword search over XML streams

2015 ◽  
Vol 11 (3) ◽  
pp. 347-369 ◽  
Author(s):  
Savong Bou ◽  
Toshiyuki Amagasa ◽  
Hiroyuki Kitagawa
Keyword(s):  
Keyword Search ◽  
Real Data ◽  
Experimental Results ◽  
Data Set ◽  
Content Type ◽  
Finite Automation ◽  
Powerful Means ◽  
Extensible Markup ◽  
Xml Streams ◽  
Better Than

Purpose – In purpose of this paper is to propose a novel scheme to process XPath-based keyword search over Extensible Markup Language (XML) streams, where one can specify query keywords and XPath-based filtering conditions at the same time. Experimental results prove that our proposed scheme can efficiently and practically process XPath-based keyword search over XML streams. Design/methodology/approach – To allow XPath-based keyword search over XML streams, it was attempted to integrate YFilter (Diao et al., 2003) with CKStream (Hummel et al., 2011). More precisely, the nondeterministic finite automation (NFA) of YFilter is extended so that keyword matching at text nodes is supported. Next, the stack data structure is modified by integrating set of NFA states in YFilter with bitmaps generated from set of keyword queries in CKStream. Findings – Extensive experiments were conducted using both synthetic and real data set to show the effectiveness of the proposed method. The experimental results showed that the accuracy of the proposed method was better than the baseline method (CKStream), while it consumed less memory. Moreover, the proposed scheme showed good scalability with respect to the number of queries. Originality/value – Due to the rapid diffusion of XML streams, the demand for querying such information is also growing. In such a situation, the ability to query by combining XPath and keyword search is important, because it is easy to use, but powerful means to query XML streams. However, none of existing works has addressed this issue. This work is to cope with this problem by combining an existing XPath-based YFilter and a keyword-search-based CKStream for XML streams to enable XPath-based keyword search.

Dynamic supplier selection through optimal ranking under two-echelon system

2019 ◽  
Vol 26 (8) ◽  
pp. 2574-2607 ◽  
Author(s):  
Md Tanweer Ahmad ◽  
Sandeep Mondal
Keyword(s):  
Supplier Selection ◽  
Real Data ◽  
Optimal Order ◽  
Asymmetric Mode ◽  
Data Set ◽  
Content Type ◽  
Weight Percentage ◽  
Competitive Edge ◽  
Order Quantities ◽  
Optimal Ranking

Purpose With the increasing competition among the industries, they remain under pressure as how to select the best set of suppliers for the competitive edge. Often, it has been challenging to develop an effective set of suppliers due to varied and asymmetric mode of criteria. The purpose of this paper is to develop a responsive chain under original equipment manufacturer (OEM). Design/methodology/approach This study proposes a responsive chain under a two-echelon system (TES) of OEM, which needs to collaborate with a set of suppliers at each echelon through an integrated methodology of AHP and TOPSIS. According to the OEM’s criteria, demands and suppliers’ capacity vary with time, therefore they are not static for a longer period. Hence, supplier selection (SS) problem possesses dynamicity in real practice. For this, MILP is used for finding optimal order quantities based on the optimal ranking at each echelon in the multi-period scenario. Subsequently, sensitivity analysis (SA) is conducted through Taguchi method of parameter design (TMPD) to achieve an optimal ranking in the TES. Findings This study suggests optimal criteria’s weight, percentage contribution, and flexibility for the suppliers and manufacturers involving through maximum demand strategy at each echelon of OEM. It also provides robust group of suppliers and manufacturers in the TES through optimal ranking and simultaneously in the order allocations. Furthermore, it restricts the number of suppliers and manufactures at each echelon through proposed methodology to obtain the solution in a very short running time. Originality/value To validate this model, a real data set for the case of chain conveyor company is used. This adopted methodology can suggest the organization that how the approach should be implemented.

A QoS-sensitive model for e-commerce customer behavior

2017 ◽  
Vol 11 (4) ◽  
pp. 380-397 ◽  
Author(s):  
Hoda Ghavamipoor ◽  
S. Alireza Hashemi Golpayegani ◽  
Maryam Shahpasand
Keyword(s):  
Service Quality ◽  
Process Mining ◽  
Real Data ◽  
Absolute Error ◽  
Customer Behavior ◽  
Behavior Modeling ◽  
Measurement Scale ◽  
Data Set ◽  
Content Type ◽  
High Level

Purpose In this paper, a Quality of Service-sensitive customer behavior model graph (QoS-CBMG) is proposed for use in service quality adaptation in e-commerce systems. Success in achieving customer satisfaction and maximizing profit in e-commerce is highly dependent on the QoS provided. However, providing high-level QoS for all customers in all Web sessions is often deemed costly and inefficient. Therefore, a QoS-sensitive model for formulating QoS-aware offers to customers is required. The paper aims to respond to this necessity. Design/methodology/approach Process mining is adopted as the knowledge extraction technique for developing a QoS-CBMG. If it is assumed that user navigation on a website is a process, then clickstreams during one user’s navigations can be considered process steps. Findings The application of both QoS-CBMG (the new model) and CBMG (the classic version) to the same real data set demonstrated that the proposed method outperforms CBMG due to its reduction of average absolute error in the measurement scale. This finding also verifies the assumption that customer behavior is sensitive to the level of QoS. Research limitations/implications From a theoretical viewpoint, the obtained QoS-CBMG facilitates the adaption in e-commerce systems, which leads to conduct the user to the desired behavior by tuning QoS levels in different Web sessions in a dynamic manner. This implication is due to the fact that QoS-CBMG can predict the upcoming clickstream of the customer at different QoS levels. Practical implications Using the proposed model for the adaptation of service quality in e-commerce websites not only results in the efficient management of the provider’s resources but also encourages customer purchases from the website and increases profitability. It is noteworthy that with the advent of cloud computing, e-commerce websites are enabled to provide various levels of QoS for their customers by supplying their basic services (e.g. infrastructure, platform) through cloud platforms. Originality/value According to the best of our knowledge, no previous model has taken into account the QoS dimension for customer behavior modeling. The main contribution of this paper is to propose a CBMG that is sensitive to the QoS provided to customers during their navigation to formulate QoS-aware offers to them.

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