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Articles 5611 - 5640 of 7256
Full-Text Articles in Computer Sciences
An Infrastructure For Performance Measurement And Comparison Of Information Retrieval Solutions, Gary Saunders
An Infrastructure For Performance Measurement And Comparison Of Information Retrieval Solutions, Gary Saunders
Theses and Dissertations
The amount of information available on both public and private networks continues to grow at a phenomenal rate. This information is contained within a wide variety of objects, including documents, e-mail archives, medical records, manuals, pictures and music. To be of any value, this data must be easily searchable and accessible. Information Retrieval (IR) is concerned with the ability to find and gain access to relevant information. As electronic data repositories continue to proliferate, so too, grows the variety of methods used to locate and access the information contained therein. Similarly, the introduction of innovative retrieval strategies—and the optimization of …
Tcruzikb: Enabling Complex Queries For Genomic Data Exploration, Pablo N. Mendes, Bobby Mcknight, Amit P. Sheth, Jessica C. Kissinger
Tcruzikb: Enabling Complex Queries For Genomic Data Exploration, Pablo N. Mendes, Bobby Mcknight, Amit P. Sheth, Jessica C. Kissinger
Kno.e.sis Publications
We developed a novel analytical environment to aid in the examination of the extensive amount of interconnected data available for genome projects. Our focus is to enable flexibility and abstraction from implementation details, while retaining the expressivity required for post-genomic research. To achieve this goal, we associated genomics data to ontologies and implemented a query formulation and execution environment with added visualization capabilities. We use ontology schemas to guide the user through the process of building complex queries in a flexible Web interface. Queries are serialized in SPARQL and sent to servers via Ajax. A component for visualization of the …
Text Analytics For Semantic Computing - The Good, The Bad And The Ugly, Meenakshi Nagarajan, Cartic Ramakrishnan, Amit P. Sheth
Text Analytics For Semantic Computing - The Good, The Bad And The Ugly, Meenakshi Nagarajan, Cartic Ramakrishnan, Amit P. Sheth
Kno.e.sis Publications
This tutorial was give at the Second IEEE International Conference on Semantic Computing Santa Clara, CA, USA - August 4-7, 2008.
E-Transcript Web Services System Supporting Dynamic Conversion Between Xml And Edi, Myungjae Kwak '11, Woohyun Kang '14, Gondy Leroy, Samir Chatterjee
E-Transcript Web Services System Supporting Dynamic Conversion Between Xml And Edi, Myungjae Kwak '11, Woohyun Kang '14, Gondy Leroy, Samir Chatterjee
CGU Faculty Publications and Research
As XML becomes a standard for communications between distributed heterogeneous machines, many schools plan to implement Web Services systems using the XML e-transcript (electronic transcript) standard. We propose a framework that supports both XML e-transcript Web Services and existing EDI e-transcript systems. The framework uses the workflow engine to exploit the benefits of workflow management mechanisms. The workflow engine manages the e-transcript business process by enacting and completing the tasks and sub-processes within the main business process. We implemented the proposed framework by using various open source projects including Java, Eclipse, and Apache Software Foundation’s Web Services projects. Compared with …
Connectionist Model Generation: A First-Order Approach, Sebastian Bader, Pascal Hitzler, Steffen Holldobler
Connectionist Model Generation: A First-Order Approach, Sebastian Bader, Pascal Hitzler, Steffen Holldobler
Computer Science and Engineering Faculty Publications
Knowledge-based artificial neural networks have been applied quite successfully to propositional knowledge representation and reasoning tasks. However, as soon as these tasks are extended to structured objects and structure-sensitive processes as expressed e.g., by means of first-order predicate logic, it is not obvious at all what neural-symbolic systems would look like such that they are truly connectionist, are able to learn, and allow for a declarative reading and logical reasoning at the same time. The core method aims at such an integration. It is a method for connectionist model generation using recurrent networks with feed-forward core. We show in this …
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Research Collection School Of Computing and Information Systems
Data mining tasks in P2P are bound by issues like scalability, peer dynamism, asynchronism, and data privacy preservation. These challenges pose difficulties for deploying conventional machine learning techniques in P2P networks, which may be hard to achieve classification accuracies comparable to regular centralized solutions. We recently investigated the classification problem in P2P networks and proposed a novel P2P classification approach by cascading Reduced Support Vector Machines (RSVM). Although promising results were obtained, the existing solution has some drawback of redundancy in both communication and computation. In this paper, we present a new approach to over the limitation of the previous …
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Research Collection School Of Computing and Information Systems
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from which test examples are to be drawn. The task can be especially difficult when the training examples are from one or several domains different from the test domain. In this paper, we propose a locally weighted ensemble framework to combine multiple models for transfer learning, where the weights are dynamically assigned according to a model's predictive power on each test example. It can integrate the advantages of various learning algorithms and the labeled information from multiple …
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online search engines. A breached server that is not detected in time may return incorrect results to the users. To prevent that, we introduce a methodology for generating an integrity proof for each search result. Our solution is targeted at search engines that perform similarity-based document retrieval, and utilize an inverted list implementation (as most search engines do). We formulate the properties that define a correct result, map the task of processing a text search query to adaptations of existing threshold-based …
A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang
A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The buyer-seller watermarking protocol enables a seller to successfully identify a traitor from a pirated copy, while preventing the seller from framing an innocent buyer. Based on finite field theory and the homomorphic property of public key cryptosystems such as RSA, several buyer-seller watermarking protocols (N. Memon and P. W. Wong (2001) and C.-L. Lei et al. (2004)) have been proposed previously. However, those protocols require not only large computational power but also substantial network bandwidth. In this paper, we introduce a new buyer-seller protocol that overcomes those weaknesses by managing the watermarks. Compared with the earlier protocols, ours is …
Mediatability: Estimating The Degree Of Human Involvement In Xml Schema Mediation, Karthik Gomadam, Ajith Harshana Ranabahu, Lakshmish Ramaswamy, Amit P. Sheth, Kunal Verma
Mediatability: Estimating The Degree Of Human Involvement In Xml Schema Mediation, Karthik Gomadam, Ajith Harshana Ranabahu, Lakshmish Ramaswamy, Amit P. Sheth, Kunal Verma
Kno.e.sis Publications
Mediation and integration of data are significant challenges because the number of services on the Web, and heterogeneities in their data representation, continue to increase rapidly. To address these challenges we introduce a new measure, mediatability, which is a quantifiable and computable metric for the degree of human involvement in XML schema mediation. We present an efficient algorithm to compute mediatability and an experimental study to analyze how semantic annotations affect the ease of mediating between two schemas. We validate our approach by comparing mediatability scores generated by our system with user-perceived difficulty. We also evaluate the scalability of our …
An Xml-Based Approach To Handling Tables In Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni
An Xml-Based Approach To Handling Tables In Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni
Kno.e.sis Publications
We explore application of XML technology for handling tables in legacy semi-structured documents. Specifically, we analyze annotating heterogeneous documents containing tables to obtain a formalized XML Master document that improves traceability (hence easing verification and update) and enables manipulation using XSLT stylesheets. This approach is useful when table instances far outnumber distinct table types because the effort required to annotate a table instance is relatively less compared to formalizing table processing that respects table’s semantics. This work is also relevant for authoring new documents with tables that should be accessible to both humans and machines.
Applications Of Voting Theory To Information Mashups, Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo
Applications Of Voting Theory To Information Mashups, Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo
Kno.e.sis Publications
Blogs, discussion forums and social networking sites are an excellent source for people's opinions on a wide range of topics. We examine the application of voting theory to "information mashups" - the combining and summarizing of data from the multitude of often-conflicting sources. This paper presents an information mashup in the music domain: a Top 10 artist chart based on user comments and listening behavior from several Web communities. We consider different voting systems as algorithms to combine opinions from multiple sources and evaluate their effectiveness using social welfare functions. Different voting schemes are found to work better in some …
Impacts Of Social Network Structure On Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau
Impacts Of Social Network Structure On Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
The study examines the relationship between social network structure and knowledge sharing in Open Source Software (OSS) development teams. One hundred and fifty projects were selected from SourceForge.net using stratified sampling. Social network structure was measured by two indices: degree of centralization and core/periphery fitness. Knowledge sharing was measured from two aspects: the quality of knowledge sharing that is indicated by the helpfulness of messages and the quantity of knowledge sharing that is indicated by the number of messages. The results show that social network structure significantly affects the quantity of knowledge sharing. However, social network structure does not influence …
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Variations exist among information system (IS) users’ abilities to effectively utilize an IS. Some users are able to maximize IS potential, while others are not. This research proposes to understand the attributes of individuals who are most capable of exploiting IS to its fullest potential as well as the management and organizational factors that facilitate the development of highly competent users. The Repertory Grid Technique was utilized to identify user attributes contributing to IS proficiency in Phase One of this research and will be utilized to identify management and organizational factors in Phase Two. The results will provide a comprehensive …
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Service Oriented Architecture (SOA) has become flavor du jour for many businesses. Seemingly, almost every company has implemented, is in the midst of implementing or is seriously considering a SOA project. A critical question many organizations are facing now is – what are the critical success factors for SOA implementations? This research aims to identify a list of factors relating to SOA implementation success. A Delphi study forms the research method, and inputs regarding SOA critical success factors are requested from a panel of experts.
Integrating Lightweight Systems Analysis Into The Unified Process By Using Service Responsibility Tables, X. Tan, S. Alter, Keng Siau
Integrating Lightweight Systems Analysis Into The Unified Process By Using Service Responsibility Tables, X. Tan, S. Alter, Keng Siau
Research Collection School Of Computing and Information Systems
This paper is a step toward establishing direct, but non-automatic links between lightweight (semi-formal) analysis methods for business professionals and heavyweight analysis methods for IT professionals. After noting the importance of user involvement in obtaining accurate and meaningful user requirements, the paper summarizes the Unified Process, a software development methodology that employs Unified Modeling Language (UML). Another section in the paper summarizes previous extensions of the work system method that produced a lightweight analysis tool called Service Responsibility Tables (SRTs). This paper uses a straightforward example to demonstrate a set of heuristics for translating between service responsibility tables produced by …
Dependence Of Binary Associations On Co-Occurrence Granularity In News Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik
Dependence Of Binary Associations On Co-Occurrence Granularity In News Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik
Kno.e.sis Publications
We describe and formalize an approach to correlate binary associations (such as between entities and events, between persons and events, etc.) implied by News documents on the co-occurrence granularity (such as document-level, paragraph-level, sentence-level, etc.) of the corresponding text phrases in the documents. Specifically, we present both qualitative and quantitative characterization of searching News documents: former in terms of the nature of the content and the queries, and latter in terms of a metric obtained by adapting the notions of precision and recall. Specifically, the approach tries to reduce the manual effort required to analyze the News documents to compare …
Semantic Web: Promising Technologies, Current Applications & Future Directions, Amit P. Sheth
Semantic Web: Promising Technologies, Current Applications & Future Directions, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing network model for the fusion of multimedia information. By synchronizing the encoding of information across multiple media channels, the neural model known as fusion Adaptive Resonance Theory (fusion ART) generates clusters that encode the associative mappings across multimedia information in a real-time and continuous manner. In addition, by incorporating a semantic category channel, fusion ART further enables multimedia information to be fused into predefined themes or semantic categories. We illustrate the fusion ART’s functionalities through experiments on two multimedia data sets in the terrorist domain and show the viability of the proposed approach.
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Research Collection School Of Computing and Information Systems
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the global optimum.
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A number of kernel learning algorithms have been proposed to learn kernel functions or matrices from side information (e.g., either labeled examples or pairwise constraints). However, most previous studies are limited to “passive” kernel learning in which side information is provided beforehand. In this paper we present a framework of Active Kernel Learning (AKL) that actively identifies the most informative pairwise constraints for kernel learning. The key challenge of active kernel learning is how to measure the informativeness of an example pair given its …
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance by combining the outputs from multiple ranking algorithms. Many ensemble ranking approaches employ supervised learning techniques to learn appropriate weights for combining multiple rankers. The main shortcoming with these approaches is that the learned weights for ranking algorithms are query independent. This is suboptimal since a ranking algorithm could perform well for certain queries but poorly for others. In this paper, we propose a novel semi-supervised ensemble ranking (SSER) algorithm that learns query-dependent weights when combining …
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Comments left by readers on Web documents contain valuable information that can be utilized in different information retrieval tasks including document search, visualization, and summarization. In this paper, we study the problem of comments-oriented document summarization and aim to summarize a Web document (e.g., a blog post) by considering not only its content, but also the comments left by its readers. We identify three relations (namely, topic, quotation, and mention) by which comments can be linked to one another, and model the relations in three graphs. The importance of each comment is then scored by: (i) graph-based method, where the …
Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Research Collection School Of Computing and Information Systems
Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous emerging fields, such as location based services and sensor networks. Since the k-medoid problem is NP hard, all existing work deals with approximate solutions on relatively small datasets. This paper aims at efficient methods for very large spatial databases, motivated by: (i) the high and ever increasing availability of spatial data, and (ii) the need for novel query types and improved services. The proposed solutions exploit the intrinsic grouping properties of a data partition index in order …
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Given a set of data points P and a query point q in a multidimensional space, Reverse Nearest Neighbor (RNN) query finds data points in P whose nearest neighbors are q. Reverse k-Nearest Neighbor (RkNN) query (where k ≥ 1) generalizes RNN query to find data points whose kNNs include q. For RkNN query semantics, q is said to have influence to all those answer data points. The degree of q's influence on a data point p (∈ P) is denoted by κp where q is the κp-th NN of p. We introduce a new variant of RNN query, namely, …
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
Research Collection School Of Computing and Information Systems
This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of ervicespecific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and …
Description Logic Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Description Logic Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Computer Science and Engineering Faculty Publications
We introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ – the basis for the ongoing standardisation of OWL 2 – can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ …
Boosting With Incomplete Information, Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao
Boosting With Incomplete Information, Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao
Kno.e.sis Publications
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we present a boosting approach that integrates features with incomplete information and those with complete information to form a strong classifier. By introducing hidden variables to model missing information, we form loss functions that combine fully labeled data with partially labeled data to effectively learn normalized and unnormalized models. The primal problems of the proposed optimization problems with these loss functions are provided to show their close relationship and the motivations behind them. …
Information Technology’S Influence On Productivity, Jason Smith
Information Technology’S Influence On Productivity, Jason Smith
Student Work
Previous research has had mixed results correlating information technology investments to increases in productivity. This research surveyed the perceptions of information technology managers to determine the impact that information technology, decentralized decision making, and improved business processes have on productivity. It concluded that information technology’s influence on productivity is to magnify the effect of decentralized decision making and improved business processes.
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Research Collection School Of Computing and Information Systems
While mobile computing provides organizations with many information systems implementation alternatives, it is often difficult to predict the potential benefits, limitations, and problems with mobile applications. Given the inherent portability of mobile devices, many design and use issues can arise which do not exist with desktop systems. While many existing rules of thumb for design of stationary systems apply to mobile systems, many new ones emerge. Issues such as the security and privacy of information take on new dimensions, and potential conflicts can develop when a single mobile device serves both personal and business needs. This paper identifies potential issues …