Digital Commons Network^™

A Survey And Taxonomy Of Sequential Recommender Systems For E-Commerce Product Recommendation, Mahreen Nasir, C. I. Ezeife

Computer Science Publications

E-commerce recommendation systems facilitate customers’ purchase decision by recommending products or services of interest (e.g., Amazon). Designing a recommender system tailored toward an individual customer’s need is crucial for retailers to increase revenue and retain customers’ loyalty. As users’ interests and preferences change with time, the time stamp of a user interaction (click, view or purchase event) is an important characteristic to learn sequential patterns from these user interactions and, hence, understand users’ long- and short-term preferences to predict the next item(s) for recommendation. This paper presents a taxonomy of sequential recommendation systems (SRecSys) with a focus on e-commerce product …

A Survey Of Sequential Pattern Based E-Commerce Recommendation Systems, Christie I. Ezeife, Hemni Karlapalepu

Computer Science Publications

E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems’ accuracy can be improved if complex sequential patterns of user purchase behavior are learned by integrating sequential patterns of customer clicks and/or purchases into the user–item rating matrix input of collaborative filtering. This review focuses on algorithms of existing E-commerce recommendation systems that are sequential pattern-based. It provides a comprehensive and comparative performance analysis of these systems, exposing their methodologies, achievements, limitations, and potential for solving more important problems in this domain. The review shows that integrating sequential pattern mining …

Battery Parameter Analysis Through Electrochemical Impedance Spectroscopy At Different State Of Charge Levels, Yuchao Wu, Sneha Sundaresan, Balakumar Balasingam

Computer Science Publications

This paper presents a systematic approach to extract electrical equivalent circuit model (ECM) parameters of the Li-ion battery (LIB) based on electrochemical impedance spectroscopy (EIS). Particularly, the proposed approach is suitable to practical applications where the measurement noise can be significant, resulting in a low signal-to-noise ratio. Given the EIS measurements, the proposed approach can be used to obtain the ECM parameters of a battery. Then, a time domain approach is employed to validate the accuracy of estimated ECM parameters. In order to investigate whether the ECM parameters vary as the battery’s state of charge (SOC) changes, the EIS experiment …

Semantic Enhanced Markov Model For Sequential E-Commerce Product Recommendation, Mahreen Nasir, C. I. Ezeife

Computer Science Publications

To model sequential relationships between items, Markov Models build a transition probability matrix P of size n× n, where n represents number of states (items) and each matrix entry p(i,j) represents transition probabilities from state i to state j. Existing systems such as factorized personalized Markov chains (FPMC) and fossil either combine sequential information with user preference information or add the high-order Markov chains concept. However, they suffer from (i) model complexity: an increase in Markov Model’s order (number of states) and separation of sequential pattern and user preference matrices, (ii) sparse transition probability matrix: few product purchases from thousands …

Survey Of Multiple Clouds: Classification, Relationships And Privacy Concerns, Reem Al-Saidi, Ziad. Kobti

Computer Science Publications

When major Cloud Service Providers (CSPs) network with other CSPs, they show a predominant area over cloud computing architecture, each with different roles to serve user demands better. This creates multiple clouds computing environments, which overcome the limitations of cloud computing and bring a wide range of benefits (e.g., avoiding vendor lock-in problem). Numerous applications can use various multiple clouds types depending on their specifications and needs. Deploying multiple clouds under hybrid or public models has introduced various privacy concerns that affect users and their data in a specific application domain. To understand the nuances of these concerns, the present …

Performance Analysis Of Empirical Open-Circuit Voltage Modeling In Lithium-Ion Batteries, Part-3: Experimental Results, Prarthana Pillai, James Nguyen, Balakumar Balasingam

Computer Science Publications

This paper is the third part of a series of papers about empirical approaches to open circuit voltage (OCV) modeling of lithium-ion batteries. The first part of the series proposed models to quantify various sources of uncertainties in the OCV models; the second part of the series presented systematic data collection approaches to compute the uncertainties in the OCV to state of charge (SOC) models. This paper uses data collected from 28 OCV characterization experiments, performed according to the data collection plan presented in the second part, to compute and analyze three OCV uncertainty metrics: cell-to-cell variations, C-Rate error, and …

A Comprehensive Literature Review On Convolutional Neural Networks, Ehsan Ur Rahman Mohammed, Narasimha Reddy Soora Dr., Sharfuddin Waseem Mohammed

Computer Science Publications

The fields of computer vision and image processing from their initial days have been dealing with the problems of visual recognition. Convolutional Neural Networks (CNNs) in machine learning are deep architectures built as feed-forward neural networks or perceptrons, which are inspired by the research done in the fields of visual analysis by the visual cortex of mammals like cats. This work gives a detailed analysis of CNNs for the computer vision tasks, natural language processing, fundamental sciences and engineering problems along with other miscellaneous tasks. The general CNN structure along with its mathematical intuition and working, a brief critical commentary …

Improving E-Commerce Product Recommendation Using Semantic Context And Sequential Historical Purchases, Mahreen Nasir, C. I. Ezeife, Abdulrauf Gidado

Computer Science Publications

Collaborative Filtering (CF)-based recommendation methods suffer from (i) sparsity (have low user–item interactions) and (ii) cold start (an item cannot be recommended if no ratings exist). Systems using clustering and pattern mining (frequent and sequential) with similarity measures between clicks and purchases for next-item recommendation cannot perform well when the matrix is sparse, due to rapid increase in number of items. Additionally, they suffer from: (i) lack of personalization: patterns are not targeted for a specific customer and (ii) lack of semantics among recommended items: they can only recommend items that exist as a result of a matching rule generated …

Emerging Challenges In Smart Grid Cybersecurity Enhancement: A Review, Fazel Mohammadi

Electrical and Computer Engineering Publications

In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is …

A Modern Copyright Framework For The Internet Of Things (Iot): Intellectual Property Scholars' Joint Submission To The Canadian Government Consultation, Pascale Chapdelaine, Anthony D. Rosborough, Aaron Perzanowski, Bita Amani, Sara Bannerman, Carys J. Craig, Lucie Guibault, Cameron J. Hutchison, Ariel Katz, Alexandra Mogyoros, Graham J. Reynolds, Teresa Scassa, Myra Tawfik

Law Publications

In response to the Canadian government consultation process on the modernization of the copyright framework launched in the summer 2021, we hereby present our analysis and recommendations concerning the interaction between copyright and the Internet of Things (IoT). The recommendations herein reflect the shared opinion of the intellectual property scholars who are signatories to this brief. They are informed by many combined decades of study, teaching, and practice in Canadian, US, and international intellectual property law.

In what follows, we explain:

•The importance of approaching the questions raised in the consultation with a firm commitment to maintaining the appropriate balance …

Mining Integrated Sequential Patterns From Multiple Databases, C. I. Ezeife, Vignesh Aravindan, Ritu Chaturvedi

Computer Science Publications

Existing work on multiple databases (MDBs) sequential pattern mining cannot mine frequent sequences to answer exact and historical queries from MDBs having different table structures. This article proposes the transaction id frequent sequence pattern (TidFSeq) algorithm to handle the difficult problem of mining frequent sequences from diverse MDBs. The TidFSeq algorithm transforms candidate 1-sequences to get transaction subsequences where candidate 1-sequences occurred as (1-sequence, itssubsequenceidlist) tuple or (1-sequence, position id list). Subsequent frequent i-sequences are computed using the counts of the sequence ids in each candidate i-sequence position id list tuples. An extended version of the general sequential pattern (GSP)-like …

Response Time And Eye Tracking Datasets For Activities Demanding Varying Cognitive Load, Prarthana Pillai, Prathamesh Ayare, Balakumar Balasingam, Kevin Milne, Francesco Biondi

Human Kinetics Publications

The dataset contains the following three measures that are widely used to determine cognitive load in humans: Detection Response Task - response time, pupil diameter, and eye gaze. These measures were recorded from 28 participants while they underwent tasks that are designed to permeate three different cognitive difficulty levels. The dataset will be useful to those researchers who seek to employ low cost, non-invasive sensors to detect cognitive load in humans and to develop algorithms for human-system automation. One such application is found in Advanced Driver Assistance Systems where eye-trackers are employed to monitor the alertness of the drivers. The …

Bias Correction In Small Sample From Big Data, Jianguo Lu, Dingding Li

Computer Science Publications

This paper discusses the bias problem when estimating the population size of big data such as online social networks (OSN) using simple random walk. Unlike the traditional estimation problem where the sample size is not very small relative to the data size, in big data a small sample relative to the data size is already very large and costly to obtain. When small samples are used, there is a bias that is no longer negligible. This paper shows analitically that the relative bias can be approximated by the reciprocal of the number of collisions, thereby a bias correction estimator is …

A Fully Automatic Gridding Method For Cdna Microarray Images, Luis Rueda, Iman Rezaeian

Computer Science Publications

Background

Processing cDNA microarray images is a crucial step in gene expression analysis, since any errors in early stages affect subsequent steps, leading to possibly erroneous biological conclusions. When processing the underlying images, accurately separating the sub-grids and spots is extremely important for subsequent steps that include segmentation, quantification, normalization and clustering.

Results

We propose a parameterless and fully automatic approach that first detects the sub-grids given the entire microarray image, and then detects the locations of the spots in each sub-grid. The approach, first, detects and corrects rotations in the images by applying an affine transformation, followed by a …

Ranking Bias In Deep Web Size Estimation Using Capture Recapture Method, Jianguo Lu

Computer Science Publications

Many deep web data sources are ranked data sources, i.e., they rank the matched documents and return at most the top k number of results even though there are more than k documents matching the query. While estimating the size of such ranked deep web data source, it is well known that there is a ranking bias—the traditional methods tend to underestimate the size when queries overflow (match more documents than the return limit). Numerous estimation methods have been proposed to overcome the ranking bias, such as by avoiding overflowing queries during the sampling process, or by adjusting the initial …

Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton

CRRAR Publications

In this paper, several examples from the literature, and one central new one, are used as case studies of texts of discourse containing an argumentation scheme that has now been widely investigated in literature on argumentation. Argumentation schemes represent common patterns of reasoning used in everyday conversational discourse. The most typical ones represent defeasible arguments based on nonmonotonic reasoning. Each scheme has a matching set of critical questions used to evaluate a particular argument fitting that scheme. The project is to study how to build a formal computational model of this scheme for the circumstantial ad hominem argument using argumentation …

Erratum: Fast Incremental Mining Of Web Sequential Patterns With Plwap Tree (Data Mining And Knowledge Discovery Doi: 10.1007/S10618-009-0133-6), C. I. Ezeife, Yi Liu

Computer Science Publications

No abstract provided.

Linear Dimensionality Reduction By Maximizing The Chernoff Distance In The Transformed Space, Luis Rueda, Myriam Herrera

Computer Science Publications

Linear dimensionality reduction (LDR) techniques are quite important in pattern recognition due to their linear time complexity and simplicity. In this paper, we present a novel LDR technique which, though linear, aims to maximize the Chernoff distance in the transformed space; thus, augmenting the class separability in such a space. We present the corresponding criterion, which is maximized via a gradient-based algorithm, and provide convergence and initialization proofs. We have performed a comprehensive performance analysis of our method combined with two well-known classifiers, linear and quadratic, on synthetic and real-life data, and compared it with other LDR techniques. The results …

Xml Schema Matching, Jianguo Lu, Ju Wang, Shengrui Wang

Computer Science Publications

XML Schema matching problem can be formulated as follows: given two XML Schemas, find the best mapping between the elements and attributes of the schemas, and the overall similarity between them. XML Schema matching is an important problem in data integration, schema evolution, and software reuse. This paper describes a matching system that can find accurate matches and scales to large XML Schemas with hundreds of nodes. In our system, XML Schemas are modeled as labeled and unordered trees, and the schema matching problem is turned into a tree matching problem. We proposed Approximate Common Structures in trees, and developed …

Multi-Robot-Based Nanoassembly Planning With Automated Path Generation, Xiaobu Yuan, Simon X. Yang

Computer Science Publications

In this paper, a novel approach of automated multirobot nanoassembly planning is presented. This approach uses an improved self-organizing map to coordinate assembly tasks of nanorobots while generating optimized motion paths at run time with a modified shunting neural network. It is capable of synchronizing multiple nanorobots working simultaneously and efficiently on the assembly of swarms of objects in the presence of obstacles and environmental uncertainty. Operation of the presented approach is demonstrated with experiments at the end of the paper.

Examination Dialogue: An Argumentation Framework For Critically Questioning An Expert Opinion, Douglas Walton

CRRAR Publications

Recent work in argumentation theory (Walton and Krabbe, 1995; Walton, 2005) and artificial intelligence (Bench-Capon, 1992, 2003; Cawsey, 1992; McBurney and Parsons, 2002; Bench-Capon and Prakken, 2005) uses types of dialogue as contexts of argument use. This paper provides an analysis of a special type called examination dialogue, in which one party questions another party, sometimes critically or even antagonistically, to try to find out what that party knows about something. This type of dialogue is most prominent in law and in both legal and non-legal arguments based on expert opinion. It is also central to dialogue systems for questioning …

Spot Detection And Image Segmentation In Dna Microarray Data, Li Qin, Luis Rueda, Ali Adnan, Alioune Ngom

Computer Science Publications

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. …

Critical Questions In Computational Models Of Legal Argument, Douglas Walton, Thomas F. Gordon

CRRAR Publications

Two recent computational models of legal argumentation, by Verheij and Gordon respectively, have interpreted critical questions as premises of arguments that can be defeated using Pollock’s concepts of undercutters and rebuttals. Using the scheme for arguments from expert opinion as an example, this paper evaluates and compares these two models of critical questions from the perspective of argumentation theory and competing legal theories about proof standardsfor defeating presumptions. The applicable proof standard is found to be a legal issue subject to argument. Verheij’smodel is shown to have problems because the proof stan-dards it applies to different kinds of premises are …

Virtual Assembly With Biologically Inspired Intelligence, Xiaobu Yuan, Simon X. Yang

Computer Science Publications

This paper investigates the introduction of biologically inspired intelligence into virtual assembly. It develops a approach to assist product engineers making assembly-related manufacturing decisions without actually realizing the physical products. This approach extracts the knowledge of mechanical assembly by allowing human operators to perform assembly operations directly in the virtual environment. The incorporation of a biologically inspired neural network into an interactive assembly planner further leads to the improvement of flexible product manufacturing, i.e., automatically producing alternative assembly sequences with robot-level instructions for evaluation and optimization. Complexity analysis and simulation study demonstrate the effectiveness and efficiency of this approach.

An Interactive Approach Of Assembly Planning, Xiaobu Yuan

Computer Science Publications

An interactive approach to assembly planning is presented. It provides a virtual reality interface for production engineers to program the virtual representation of robotic manipulators in a three-dimensional (3D) operation space. The direct human involvement creates a user-defined assembly sequence, which contains the human knowledge of mechanical assembly. By extracting the precedence relationship of machinery parts, for the first time it becomes possible to generate alternative assembly sequences automatically from a single sequence for robot reprogramming. This interactive approach introduces human expertise into assembly planning, thus breaking down the computational complexity of autonomous systems. Experiments and analysis provide strong evidence …

Extensible Information Brokers, Jianguo Lu, John Mylopoulos

Computer Science Publications

The number and size of information services available on the internet has been growing exponentially over the past few years. This growth has created an urgent need for information agents that act as brokers in the sense that they can autonomously search, gather, and integrate information on behalf of a user. To remain useful, such brokers will have to evolve throughout their lifetime to keep up with evolving and ever-changing information services. This paper proposes a framework named XIB (eXtensible Information Brokers) for building and evolving information brokers.

The XIB takes as input a description of required information services and …

Higher Order Generalization And Its Application In Program Verification, Jianguo Lu, John Mylopoulos, Masateru Harao, Masami Hagiya

Computer Science Publications

Generalization is a fundamental operation of inductive inference. While first order syntactic generalization (anti–unification) is well understood, its various extensions are often needed in applications. This paper discusses syntactic higher order generalization in a higher order language λ2 [1]. Based on the application ordering, we prove that least general generalization exists for any two terms and is unique up to renaming. An algorithm to compute the least general generalization is also presented. To illustrate its usefulness, we propose a program verification system based on higher order generalization that can reuse the proofs of similar programs.

P-Buffer: Hidden-Line Rendering With A Dynamic P-Buffer, Xiaobu Yuan, Sun Hanqiu

Computer Science Publications

Despite the emergence of highly realistic computer-generated images, line-drawing images are still a common practice in showing the shapes and movements of three-dimensional objects. It is especially true when rendering time is critical in interactive applications such as the modeling and testing stage of computer aided design/manufacturing, computer animation, and virtual reality. Hence much effort has been devoted to provide sufficient information of the displayed objects with the least amount of time. While the techniques that determine visible surfaces in an image-space have the advantages on rendering speed and processable shapes, those that decide visible lines or line segments in …

Dynamic Service Matchmaking Among Agents In Open Information Environments, Katia Sycara, Matthias Klusch, Seth Widoff, Jianguo Lu

Computer Science Publications

No abstract provided.