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Full-Text Articles in Computer Sciences
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
David LO
Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …
F-Trail: Finding Patterns In Taxi Trajectories, Yasuko Matsubara, Evangelos Papalexakis, Lei Li, David Lo, Yasushi Sakurai, Christos Faloutsos
F-Trail: Finding Patterns In Taxi Trajectories, Yasuko Matsubara, Evangelos Papalexakis, Lei Li, David Lo, Yasushi Sakurai, Christos Faloutsos
David LO
Given a large number of taxi trajectories, we would like to find interesting and unexpected patterns from the data. How can we summarize the major trends, and how can we spot anomalies? The analysis of trajectories has been an issue of considerable interest with many applications such as tracking trails of migrating animals and predicting the path of hurricanes. Several recent works propose methods on clustering and indexing trajectories data. However, these approaches are not especially well suited to pattern discovery with respect to the dynamics of social and economic behavior. To further analyze a huge collection of taxi trajectories, …
An Empirical Study On Developer Interactions In Stackoverflow, Shaowei Wang, David Lo, Lingxiao Jiang
An Empirical Study On Developer Interactions In Stackoverflow, Shaowei Wang, David Lo, Lingxiao Jiang
David LO
No abstract provided.
Mining Indirect Antagonistic Communities From Social Interactions, Kuan Zhang, David Lo, Ee Peng Lim, Philips Kokoh Prasetyo
Mining Indirect Antagonistic Communities From Social Interactions, Kuan Zhang, David Lo, Ee Peng Lim, Philips Kokoh Prasetyo
David LO
Antagonistic communities refer to groups of people with opposite tastes, opinions, and factions within a community. Given a set of interactions among people in a community, we develop a novel pattern mining approach to mine a set of antagonistic communities. In particular, based on a set of user-specified thresholds, we extract a set of pairs of communities that behave in opposite ways with one another. We focus on extracting a compact lossless representation based on the concept of closed patterns to prevent exploding the number of mined antagonistic communities. We also present a variation of the algorithm using a divide …
Analysis Of Segmentation Algorithms For Pavement Distress Images, Allen Downey, Haris N. Koutsopoulos, Ibrahim El Sanhouri
Analysis Of Segmentation Algorithms For Pavement Distress Images, Allen Downey, Haris N. Koutsopoulos, Ibrahim El Sanhouri
Allen B. Downey
Collection and analysis of pavement distress data is an important component of any pavement‐management system. Various systems are currently under development that automate this process. They consist of appropriate hardware for the acquisition of pavement distress images and, in some cases, software for the analysis of the collected data. An important step in the automatic interpretation of images is segmentation, the process of extracting the objects of interest (distresses) from the background. We examine algorithms for segmenting pavement images and evaluate their effectiveness in separating the distresses from the background. The methods examined include the Otsu method, Kittler's method, a …
Primitive-Based Classification Of Pavement Cracking Images, Allen Downey
Primitive-Based Classification Of Pavement Cracking Images, Allen Downey
Allen B. Downey
Collection and analysis of pavement distress data are receiving attention for their potential to improve the quality of information on pavement condition. We present an approach for the automated classificaton of asphalt pavement distresses recorded on video or photographic film. Based on a model that describes the statistical properties of pavement images, we develop algorithms for image enhancement, segmentation, and distress classification. Image enhancement is based on subtraction of an “average” background: segmentation assigns one of four possible values to pixels based on their likelihood of belonging to the object. The classification approach proceeds in two steps: in the first …
Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu
Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu
David LO
With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has become increasingly important. Yet the existing pattern mining methods cannot offer the efficiency desirable for large pattern discovery. We propose Spider- Mine, a novel algorithm to efficiently mine top-K largest frequent patterns from a single massive network with any user-specified probability of 1 − ϵ. Deviating from the existing edge-by-edge (i.e., incremental) pattern-growth framework, SpiderMine achieves its efficiency by unleashing the power of small patterns of a bounded diameter, which we call “spiders”. With the spider structure, our approach adopts a …
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
David LO
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.
Benchmarking Multimedia Databases, Arcot Desai Narasimhalu, Mohan S. Kankanhalli, Kang Wu Jian
Benchmarking Multimedia Databases, Arcot Desai Narasimhalu, Mohan S. Kankanhalli, Kang Wu Jian
Arcot Desai NARASIMHALU
Multimedia technologies are being adopted both in the professional and commercial world with great enthusiasm. This has led to a significant interest in the research and development of multimedia databases. However, none of these efforts have really addressed the issues related to the benchmarking of multimedia databases. We analyze the problem of benchmarking multimedia databases in this paper and suggest a methodology
Colour Matching For Imaging Retrieval, Babu M. Mehtre, Mohan S. Kankanhalli, Arcot Desai Narasimhalu, Guo Chang Man
Colour Matching For Imaging Retrieval, Babu M. Mehtre, Mohan S. Kankanhalli, Arcot Desai Narasimhalu, Guo Chang Man
Arcot Desai NARASIMHALU
Color is an important attribute for image matching and retrieval. We present two new color matching methods, the Reference Color Table Method and a Distance Method, for image retrieval. Both these methods and an existing method Histogram Intersection were implemented and tested for a database size of 170 color images. To compare the efficacy of each method, a figure of merit, called Efficiency of Retrieval, is defined. The results show that both the new methods perform better than the existing method, and that the Reference Color Table Method gives the best results.
Fuzzy Content-Based Retrieval In Image Databases, Kang Wu Jian, Arcot Desai Narasimhalu
Fuzzy Content-Based Retrieval In Image Databases, Kang Wu Jian, Arcot Desai Narasimhalu
Arcot Desai NARASIMHALU
Image data are inherently visual. The description of visual characteristics of images are imprecise. Fuzzy retrieval of images stored in a feature-based image database is a natural means to access the data. Unfortunately, to the authors knowledge, little work has been done on fuzzy image database models and fuzzy retrieval of feature-based image databases. In this paper, a fuzzy image database model and a concept of fuzzy space are proposed and fuzzy query processing in fuzzy space and fuzzy indexing on complex fuzzy vectors are described. An example image database, the computer-aided facial image inference and retrieval system (CAFIIR), is …