Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (6876)
- Computer Sciences (6868)
- Databases and Information Systems (2875)
- Software Engineering (2164)
- Artificial Intelligence and Robotics (1253)
-
- Engineering (957)
- Numerical Analysis and Scientific Computing (844)
- Information Security (709)
- Graphics and Human Computer Interfaces (627)
- Social and Behavioral Sciences (570)
- Computer Engineering (512)
- Business (461)
- Operations Research, Systems Engineering and Industrial Engineering (418)
- Theory and Algorithms (387)
- Programming Languages and Compilers (333)
- OS and Networks (259)
- Communication (239)
- Social Media (194)
- Public Affairs, Public Policy and Public Administration (186)
- Data Storage Systems (176)
- Transportation (170)
- Education (152)
- Medicine and Health Sciences (140)
- Digital Communications and Networking (123)
- Management Information Systems (98)
- Computer and Systems Architecture (89)
- International and Area Studies (89)
- Asian Studies (88)
- Health Information Technology (83)
- Technology and Innovation (78)
- Keyword
-
- Deep learning (112)
- Machine learning (107)
- Social media (63)
- Data mining (59)
- Reinforcement learning (58)
-
- Artificial intelligence (55)
- Empirical study (55)
- Deep Learning (49)
- Software engineering (49)
- Optimization (47)
- Privacy (47)
- Task analysis (46)
- Cloud computing (45)
- Online learning (45)
- Visualization (45)
- Neural networks (44)
- Security (43)
- Training (43)
- Feature extraction (42)
- Anomaly detection (41)
- Collaboration (41)
- Singapore (41)
- Twitter (41)
- Large Language Models (36)
- Semantics (36)
- Android (35)
- Natural language processing (35)
- Classification (34)
- Machine Learning (33)
- Blockchain (32)
- Publication Year
- File Type
Articles 5911 - 5940 of 7017
Full-Text Articles in Entire DC Network
Why Quants Fail, M. Thulasidas
Why Quants Fail, M. Thulasidas
Research Collection School Of Computing and Information Systems
Mathematical finance is built on a couple of assumptions. The most fundamental of them is the one on ma ket efficiency. It states that the market prices every asset fairly, and that the prices contain all the information available in the market.
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Research Collection School Of Computing and Information Systems
Future Generation CDMA wireless systems, e.g., 3G, can simultaneously accommodate flow transmissions of users with widely heterogeneous applications. As radio resources are limited, we propose an admission control rule that protects users with stringent transmission bit-rate requirements (“streaming traffic”) while offering sufficient capacity over longer time intervals to delay-tolerant users (“elastic traffic”). While our strategy may not satisfy classical notions of fairness, we aim to reduce congestion and increase overall throughput of elastic users. Using time-scale decomposition, we develop approximations to evaluate the performance of our differentiated admission control strategy to support integrated services with transmission bit-rate requirements in a …
Exploiting Bilingual Information To Improve Web Search, Wei Gao, John Bitzer, Ming Zhou, Kam-Fai Wong
Exploiting Bilingual Information To Improve Web Search, Wei Gao, John Bitzer, Ming Zhou, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Web search quality can vary widely across languages, even for the same information need. We propose to exploit this variation in quality by learning a ranking function on bilingual queries: queries that appear in query logs for two languages but represent equivalent search interests. For a given bilingual query, along with corresponding monolingual query log and monolingual ranking, we generate a ranking on pairs of documents, one from each language. Then we learn a linear ranking function which exploits bilingual features on pairs of documents, as well as standard monolingual features. Finally, we show how to reconstruct monolingual ranking from …
Evaluating Straddle Carrier Deployment Policies: A Simulation Study For The Piraeus Container Terminal, Eleni Hadjiconstantinou, Nang Laik Ma
Evaluating Straddle Carrier Deployment Policies: A Simulation Study For The Piraeus Container Terminal, Eleni Hadjiconstantinou, Nang Laik Ma
Research Collection School Of Computing and Information Systems
Most container terminals in the world today are operating up to their capacities. In this paper, we have developed a decision support system to optimise yard operations by considering all container flows (import, export and transshipment) through the yard with the view to improving the terminal performance and efficiency. In another paper, we proposed an optimisation model that determines optimal container locations and straddle carrier (SC) movements with the objective of minimising the overall storage and handling cost of containers. In this paper, a discrete event simulation tool for container terminal operations has been developed with three objectives: (i) to …
Symphony: Enabling Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw
Symphony: Enabling Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw
Research Collection School Of Computing and Information Systems
We present the design of Symphony, a platform that enables non-developers to build and deploy a new class of search-driven applications that combine their data and domain expertise with content from search engines and other web services. The Symphony prototype has been built on top of Microsoft’s Live Search infrastructure. While Symphony naturally makes use of the customization capabilities exposed by Live Search, its distinguishing feature is the capability it provides to the application creator to combine their proprietary data and domain expertise with content obtained from Live Search. They can also integrate specialized data obtained from web services to …
Game Action Based Power Management For Multiplayer Online Game, Bhojan Anand, A. L. Ananda, Mun Choon Chan, Long Thanh Le, Rajesh Krishna Balan
Game Action Based Power Management For Multiplayer Online Game, Bhojan Anand, A. L. Ananda, Mun Choon Chan, Long Thanh Le, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Current mobile devices embrace a wide range of functionalities including high speed network support, hardware accelerated 3D graphics, and multimedia capabilities. These capabilities have boosted the interest for enabling multiplayer online games (MOG) support on such devices. However, the lack of similar growth in battery technology limits the usability of these devices for MOGs. In this paper, we present energy conservation techniques for highly interactive MOGs. These are games, such as first-person shooters, where crisp user interaction is paramount to the overall game experience. Hence, conserving energy while preserving crisp user interaction becomes a critical consideration in this domain. We …
Data Mining For Software Engineering, Tao Xie, Suresh Thummalapenta, David Lo, Chao Liu
Data Mining For Software Engineering, Tao Xie, Suresh Thummalapenta, David Lo, Chao Liu
Research Collection School Of Computing and Information Systems
To improve software productivity and quality, software engineers are increasingly applying data mining algorithms to various software engineering tasks. However, mining SE data poses several challenges. The authors present various algorithms to effectively mine sequences, graphs, and text from such data.
On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Research Collection School Of Computing and Information Systems
This paper studies a new form of nearest neighbor queries in spatial databases, namely, mutual nearest neighbour (MNN) search. Given a set D of objects and a query object q, an MNN query returns from D, the set of objects that are among the k1 (≥ 1) nearest neighbors (NNs) of q; meanwhile, have q as one of their k2(≥ 1) NNs. Although MNN queries are useful in many applications involving decision making, data mining, and pattern recognition, it cannot be efficiently handled by existing spatial query processing approaches. In this paper, we present …
Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Research Collection School Of Computing and Information Systems
This paper introduces and solves a novel type of spatial queries, namely, Optimal-Location-Selection (OLS) search, which has many applications in real life. Given a data object set D_A, a target object set D_B, a spatial region R, and a critical distance d_c in a multidimensional space, an OLS query retrieves those target objects in D_B that are outside R but have maximal optimality. Here, the optimality of a target object b \in D_B located outside R is defined as the number of the data objects from D_A that are inside R and meanwhile have their distances to b not exceeding …
Inferring Player Rating From Performance Data In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Muhammad Aurangzeb Ahmad, Nishith Pathak, Jaideep Srivastava
Inferring Player Rating From Performance Data In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Muhammad Aurangzeb Ahmad, Nishith Pathak, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
This paper examines online player performance in EverQuest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. The study uses the game's player performance data to devise performance metrics for online players. We report three major findings. First, we show that the game's point-scaling system overestimates performances of lower level players and underestimates performances of higher level players. We present a novel point-scaling system based on the game's player performance data that addresses the underestimation and overestimation problems. Second, we present a highly accurate predictive model for player performance as a function of past behavior. …
Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang
Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang
Research Collection School Of Computing and Information Systems
SSnetViz is an ongoing research to design and implement a visualization engine for heterogeneous semantic social networks. A semantic social network is a multi-modal network that contains nodes representing di®erent types of people or object entities, and edges representing relationships among them. When multiple heterogeneous semantic social networks are to be visualized together, SSnetViz provides a suite of functions to store heterogeneous semantic social networks, to integrate them for searching and analysis. We will illustrate these functions using social networks related to terrorism research, one crafted by domain experts and another from Wikipedia.
Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska
Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska
Research Collection School Of Computing and Information Systems
Graphical models are used to depict relevant aspects of real-world domains intended to be supported by an information system. Various approaches for modeling exist and approaches such as object-oriented and process-oriented modeling methods are in widespread use. These modeling methods differ in their expressive power as well as in their complexity of use, thereby leading to an important investment decision for organizations seeking to conduct modeling projects. In this paper, we used an established approach for evaluating the complexity of conceptual modeling methods and compared two important industry standards for modeling, Unified Modeling Language and Business Process Modeling Notation, based …
Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang
Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang
Research Collection School Of Computing and Information Systems
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we propose to use a multi-task learning method coupled with human guidance to address this weakly-supervised relation extraction problem. The proposed framework models the commonality among different relation types through a shared weight vector, enables knowledge learned from …
Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei
Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of extracting technical paraphrases from a parallel software corpus, namely, a collection of duplicate bug reports. Paraphrase acquisition is a fundamental task in the emerging area of text mining for software engineering. Existing paraphrase extraction methods are not entirely suitable here due to the noisy nature of bug reports. We propose a number of techniques to address the noisy data problem. The empirical evaluation shows that our method significantly improves an existing method by upto 58%
Setting Discrete Bid Levels Adaptively In Repeated Auctions, Jilian Zhang, Hoong Chuin Lau, Jialie Shen
Setting Discrete Bid Levels Adaptively In Repeated Auctions, Jilian Zhang, Hoong Chuin Lau, Jialie Shen
Research Collection School Of Computing and Information Systems
The success of an auction design often hinges on its ability to set parameters such as reserve price and bid levels that will maximize an objective function such as the auctioneer revenue. Works on designing adaptive auction mechanisms have emerged recently, and the challenge is in learning different auction parameters by observing the bidding in previous auctions. In this paper, we propose a non-parametric method for determining discrete bid levels dynamically so as to maximize the auctioneer revenue. First, we propose a non-parametric kernel method for estimating the probabilities of closing price with past auction data. Then a greedy strategy …
Multilayer Image Inpainting Approach Based On Neural Networks, Quan Wang, Zhaoxia Wang, Che Sau Chang, Ting Yang
Multilayer Image Inpainting Approach Based On Neural Networks, Quan Wang, Zhaoxia Wang, Che Sau Chang, Ting Yang
Research Collection School Of Computing and Information Systems
This paper describes an image inpainting approach based on the self-organizing map for dividing an image into several layers, assigning each damaged pixel to one layer, and then restoring these damaged pixels by the information of their respective layer. These inpainted layers are then fused together to provide the final inpainting results. This approach takes advantage of the neural network's ability of imitating human's brain to separate objects of an image into different layers for inpainting. The approach is promising as clearly demonstrated by the results in this paper.
Formal Verification Of Scalable Nonzero Indicators, Jun Sun, Yang Liu, Jun Sun, Jin Song Dong, Wei Chen, Yanhong A. Liu
Formal Verification Of Scalable Nonzero Indicators, Jun Sun, Yang Liu, Jun Sun, Jin Song Dong, Wei Chen, Yanhong A. Liu
Research Collection School Of Computing and Information Systems
Concurrent algorithms are notoriously difficult to design correctly, and high performance algorithms that make little or no use of locks even more so. In this paper, we describe a formal verification of a recent concurrent data structure Scalable NonZero Indicators. The algorithm supports incrementing, decrementing, and querying the shared counter in an efficient and linearizable way without blocking. The algorithm is highly non-trivial and it is challenging to prove the correctness. We have proved that the algorithm satisfies linearizability, by showing a trace refinement relation from the concrete implementation to its abstract specification. These models are specified in CSP and …
Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan
Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
User modeling is aimed at capturing the users’ interests in a working domain, which forms the basis of providing personalized information services. In this paper, we present an ontology based user model, called user ontology, for providing personalized information service in the Semantic Web. Different from the existing approaches that only use concepts and taxonomic relations for user modeling, the proposed user ontology model utilizes concepts, taxonomic relations, and non-taxonomic relations in a given domain ontology to capture the users’ interests. As a customized view of the domain ontology, a user ontology provides a richer and more precise representation of …
The Wisdom Of The Few: A Collaborative Filtering Approach Based On Expert Opinions From The Web, Xavier Amatriain, Neal Lathia, Josep M. Pujol, Haewoon Kwak, Nuria. Oliver
The Wisdom Of The Few: A Collaborative Filtering Approach Based On Expert Opinions From The Web, Xavier Amatriain, Neal Lathia, Josep M. Pujol, Haewoon Kwak, Nuria. Oliver
Research Collection School Of Computing and Information Systems
Nearest-neighbor collaborative filtering provides a successful means of generating recommendations for web users. However, this approach suffers from several shortcomings, including data sparsity and noise, the cold-start problem, and scalability. In this work, we present a novel method for recommending items to users based on expert opinions. Our method is a variation of traditional collaborative filtering: rather than applying a nearest neighbor algorithm to the user-rating data, predictions are computed using a set of expert neighbors from an independent dataset, whose opinions are weighted according to their similarity to the user. This method promises to address some of the weaknesses …
Poster Abstract: Beamcast: Harnessing Beamforming Capabilities For Link Layer Multicast, Souvik Sen, Rahul Ghosh, Jie Xiong, Romit Roy Choudhury
Poster Abstract: Beamcast: Harnessing Beamforming Capabilities For Link Layer Multicast, Souvik Sen, Rahul Ghosh, Jie Xiong, Romit Roy Choudhury
Research Collection School Of Computing and Information Systems
Wireless multicast is an important service primitive for emerging applications such as live video, streaming audio and content telecasts. Transmission rate in such a link layer multicast is bottlenecked by the rate of the weakest client, leading to channel under-utilization. Attempts to increase the data rate results in lower reliability (due to higher bit error rate) and higher unfairness. This poster utilizes smart beamforming antennas to improve multicast performance in wireless LANs. The main idea is to satisfy majority of the (strong) clients with a high-rate omnidirectional transmission, followed by high-rate directional transmission(s) to cover the weaker ones. By selecting …
Verification Of Population Ring Protocols In Pat, Yang Liu, Jun Pang, Jun Sun, Jianhua Zhao
Verification Of Population Ring Protocols In Pat, Yang Liu, Jun Pang, Jun Sun, Jianhua Zhao
Research Collection School Of Computing and Information Systems
The population protocol model has emerged as an elegant paradigm for describing mobile ad hoc networks, consisting of a number of nodes that interact with each other to carry out a computation. One essential property of self-stabilizing population protocols is that all nodes must eventually converge to the correct output value, with respect to all possible initial configurations. It has been shown that fairness constraints play a crucial role in designing population protocols. The Process Analysis Toolkit (PAT) has been developed to perform verifications under different fairness constraints efficiently. In particular, it can handle global fairness, which is required for …
A Bayesian Approach Integrating Regional And Global Features For Image Semantic Learning, Luong-Dong Nguyen, Ghim-Eng Yap, Ying Liu, Ah-Hwee Tan, Liang-Tien Chia, Joo-Hwee Lim
A Bayesian Approach Integrating Regional And Global Features For Image Semantic Learning, Luong-Dong Nguyen, Ghim-Eng Yap, Ying Liu, Ah-Hwee Tan, Liang-Tien Chia, Joo-Hwee Lim
Research Collection School Of Computing and Information Systems
In content-based image retrieval, the “semantic gap” between visual image features and user semantics makes it hard to predict abstract image categories from low-level features. We present a hybrid system that integrates global features (Gfeatures) and region features (R-features) for predicting image semantics. As an intermediary between image features and categories, we introduce the notion of mid-level concepts, which enables us to predict an image’s category in three steps. First, a G-prediction system uses G-features to predict the probability of each category for an image. Simultaneously, a R-prediction system analyzes R-features to identify the probabilities of mid-level concepts in that …
Exploring Inter-Concept Relationship With Context Space For Semantic Video Indexing, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Exploring Inter-Concept Relationship With Context Space For Semantic Video Indexing, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Semantic concept detectors are often individually and independently developed. Using peripherally related concepts for leveraging the power of joint detection, which is referred to as context-based concept fusion (CBCF), has been one of the focus studies in recent years. This paper proposes the construction of a context space and the exploration of the space for CBCF. Context space considers the global consistency of concept relationship, addresses the problem of missing annotation, and is extensible for cross-domain contextual fusion. The space is linear and can be built by modeling the inter-concept relationship through annotation provided by either manual labeling or machine …
Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo
Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The massive amount of near-duplicate and duplicate web videos has presented both challenge and opportunity to multimedia computing. On one hand, browsing videos on Internet becomes highly inefficient for the need to repeatedly fast-forward videos of similar content. On the other hand, the tremendous amount of somewhat duplicate content also makes some traditionally difficult vision tasks become simple and easy. For example, annotating pictures can be as simple as recycling the tags of Internet images retrieved from image search engines. Such tasks, of either to eliminate or to recycle near-duplicates, can usually be achieved by the nearest neighbor search of …
An Agent-Based Commodity Trading Simulation, Shih-Fen Cheng, Yee Pin Lim
An Agent-Based Commodity Trading Simulation, Shih-Fen Cheng, Yee Pin Lim
Research Collection School Of Computing and Information Systems
In this paper, an event-centric commodity trading simulation powered by the multiagent framework is presented. The purpose of this simulation platform is for training novice traders. The simulation is progressed by announcing news events that affect various aspects of the commodity supply chain. Upon receiving these events, market agents that play the roles of producers, consumers, and speculators would adjust their views on the market and act accordingly. Their actions would be based on their roles and also their private information, and collectively they shape the market dynamics. This simulation has been effectively deployed for several training sessions. We will …
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k-anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k-1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u, and forward their minimum bounding rectangle (termed anonymzing spatial region, ASR) to …
Identifying Bug Signatures Using Discriminative Graph Mining, Hong Cheng, David Lo, Yang Zhou, Xiaoyin Wang, Xifeng Yan
Identifying Bug Signatures Using Discriminative Graph Mining, Hong Cheng, David Lo, Yang Zhou, Xiaoyin Wang, Xifeng Yan
Research Collection School Of Computing and Information Systems
Bug localization has attracted a lot of attention recently. Most existing methods focus on pinpointing a single statement or function call which is very likely to contain bugs. Although such methods could be very accurate, it is usually very hard for developers to understand the context of the bug, given each bug location in isolation. In this study, we propose to model software executions with graphs at two levels of granularity: methods and basic blocks. An individual node represents a method or basic block and an edge represents a method call, method return or transition (at the method or basic …
On The Effectiveness Of Software Diversity: A Systematic Study On Real-World Vulnerabilities, Jin Han, Debin Gao, Robert H. Deng
On The Effectiveness Of Software Diversity: A Systematic Study On Real-World Vulnerabilities, Jin Han, Debin Gao, Robert H. Deng
Research Collection School Of Computing and Information Systems
Many systems have been introduced to detect software intrusions by comparing the outputs and behavior of diverse replicas when they are processing the same, potentially malicious, input. When these replicas are constructed using off-the-shelf software products, it is assumed that they are diverse and not compromised simultaneously under the same attack. In this paper, we analyze vulnerabilities published in 2007 to evaluate the extent to which this assumption is valid. We focus on vulnerabilities in application software, and show that the majority of these software products --- including those providing the same service (and therefore multiple software substitutes can be …
Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang
Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang
Research Collection School Of Computing and Information Systems
With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from different application domains. As an effective technique for organizing, browsing, and searching large data collections, music information retrieval is attracting more and more attention. How to measure and model the similarity between different music items is one of the most fundamental yet challenging research problems. In this paper, we introduce a novel framework based on a multimodal and adaptive similarity measure for various applications. Distinguished from previous approaches, our system can effectively combine music properties from different aspects into a …
Automatic Steering Of Behavioral Model Inference, David Lo, Leonardo Mariani, Mauro Pezze
Automatic Steering Of Behavioral Model Inference, David Lo, Leonardo Mariani, Mauro Pezze
Research Collection School Of Computing and Information Systems
Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and time-consuming, researchers defined several techniques to extract finite state models from code and traces. Automatically generating models requires much less effort than designing them, and thus eases the verification and validation of large software systems. However, when models are inferred automatically, the precision of the mining process is critical. Behavioral models mined with imprecise processes can include many spurious behaviors, and can thus compromise the results of testing and analysis techniques that use …