Computer Sciences Commons^™

Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

An effective relevance feedback solution plays a key role in interactive intelligent 3D object retrieval systems. In this work, we investigate the relevance feedback problem for interactive intelligent 3D object retrieval, with the focus on studying effective machine learning algorithms for improving the user's interaction in the retrieval task. One of the key challenges is to learn appropriate kernel similarity measure between 3D objects through the relevance feedback interaction with users. We address this challenge by presenting a novel framework of Active multiple kernel learning (AMKL), which exploits multiple kernel learning techniques for relevance feedback in interactive 3D object retrieval. …

Discovering Knowledge Structure In The Web, Siddharth Ramu

Master's Projects

Association Rule Mining is a widely used method for finding interesting relationships from large data sets. The challenge here is how to swiftly and accurately discover association rules from large data sets. To achieve this, this paper will (1) build a data warehouse system that simulates the secondary storage and represents a database by bit patterns, and (2) implement a new geometric algorithm to find association rules, called Maximal Simplex Algorithm. The data warehouse consists of very long bit columns. Each column is an item or an attribute value pair and a row represents a transaction or a tuple in …

Ec2lab: Saas Using Amazon Elastic Cloud Compute, Manisha Gaikwad

Master's Projects

The cloud computing is gaining popularity as it provides an infinite pool of hardware and software resources on demand. The Infrastructure-as-a-Service (IaaS) layer provides the physical resources, and relieves the users from the tedious as well as time consuming task of procuring and setting the server as well as the storage. This project harnesses the capability of the Amazon IaaS layer. The Software-as-a-Service (SaaS) application which is built on top of Amazon IaaS layer, helps the users to easily handle and connect with Amazon's Elastic Cloud Compute (EC2) instances.

Efficient Attacks On Homophonic Substitution Ciphers, Amrapali Dhavare

Master's Projects

Substitution ciphers are one of the earliest types of ciphers. Examples of classic substitution ciphers include the well-known simple substitution and the less well-known homophonic substitution. Although simple substitution ciphers are indeed simple - both in terms of their use and attacks; the homophonic substitution ciphers are far more challenging to break. Even with modern computing technology, homophonic substitution ciphers remain a significant challenge. This project focuses on designing, implementing, and testing an efficient attack on homophonic substitution ciphers. We use an iterative approach that generalizes the fastest known attack on simple substitution ciphers and also employs a heuristic search …

Chatbots In The Library: Is It Time?, Deeann Allison

University of Nebraska-Lincoln Libraries: Faculty Publications

This paper describes a pilot at the University of Nebraska-Lincoln for a chatbot that answers questions about the library and library resources. The chatbot was developed using a SQL database to store the question and answers using Artificial Intelligence Mark-up Language metadata. The user interface was built using PHP, adapted from Program-O. The open source PHP program was modified to support better display and the launching of URLs within the chatbot screen. Database content was created by “mining” library websites for information, and analyzing chat logs.

The chatbot answers questions from a variety of users from around the world. It …

Relational Neighborhood Inverse Consistency For Constraint Satisfaction, Robert J. Woodward, Shant Karakashian, Berthe Y. Choueiry, Christian Bessiere

School of Computing: Technical Reports

Freuder and Elfe [1996] introduced Neighborhood Inverse Consistency (NIC) as a new local consistency property for Constraint Satisfaction Problems (CSPs) that filters the domains of variables. Two advantages of the algorithm for enforcing NIC is that it automatically adapts its filtering power to the local connectivity of the network and has insignificant space overhead. In this document, we discuss Relational Neighborhood Inverse Consistency (RNIC), which is an extension of NIC to filter relations introduced in [Woodward et al., 2011a], how we enhance the propagation effectiveness by reformulating the dual graph of the CSP. We also describe an automated selection policy …

Verification Of Orchestration Systems Using Compositional Partial Order Reduction, Tian Huat Tan, Yang Liu, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Orc is a computation orchestration language which is designed to specify computational services, such as distributed communication and data manipulation, in a concise and elegant way. Four concurrency primitives allow programmers to orchestrate site calls to achieve a goal, while managing timeouts, priorities, and failures. To guarantee the correctness of Orc model, effective verification support is desirable. Orc has a highly concurrent semantics which introduces the problem of state-explosion to search-based verification methods like model checking. In this paper, we present a new method, called Compositional Partial Order Reduction (CPOR), which aims to provide greater state-space reduction than classic partial …

Data Mining And Data Warehouse ------ Maximal Simplex Method, Madhuri Gollu

Master's Projects

Association Rule Mining is a widely used method for finding interesting relationships from large data sets. The challenge here is how to swiftly and accurately discover association rules from large data sets. To achieve this, this paper will (1) build a data warehouse system that simulates the secondary storage and represents a database by bit patterns, and (2) implement a new geometric algorithm to find association rules, called Maximal Simplex Algorithm. The data warehouse consists of very long bit columns. Each column is an item or an attribute value pair and a row represents a transaction or a tuple in …

X10 Vs Java: Concurrency Constructs And Performance, Anh Trinh

Master's Projects

To avoid overheating the chip, chip designers have switched to multi-cores. While multicore CPUs reserve instruction-level parallelism features that help existing applications run as if they were running under single core, applications do not reach speeds two or four times faster. Instead of relying on compiler and hardware to figure out parallelism in source code, software developers now must control parallelism explicitly in their programs. Many programming languages and libraries, such as Java, C# .NET, and OpenMP, are trying to help programmers by providing rich concurrency API. X10 is the new experimental language from IBM Research, which has been under …

N-Grams Assisted Long Web Search Query Optimization, Jehann Kersi Irani

Master's Projects

Commercial search engines do not return optimal search results when the query is a long or multi-topic one [1]. Long queries are used extensively. While the creator of the long query would most likely use natural language to describe the query, it contains extra information. This information dilutes the results of a web search, and hence decreases the performance as well as quality of the results returned. Kumaran et al. [22] showed that shorter queries extracted from longer user generated queries are more effective for ad-hoc retrieval. Hence reducing these queries by removing extra terms, the quality of the search …

Differencing Labeled Transition Systems, Zhenchang Xing, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Concurrent programs often use Labeled Transition Systems (LTSs) as their operational semantic models, which provide the basis for automatic system analysis and verification. System behaviors (generated from the operational semantics) evolve as programs evolve for fixing bugs or implementing new user requirements. Even when a program remains unchanged, its LTS models explored by a model checker or analyzer may be different due to the application of different exploration methods. In this paper, we introduce a novel approach (named SpecDiff) to computing the differences between two LTSs, representing the evolving behaviors of a concurrent program. SpecDiff considers LTSs as Typed Attributed …

An Exploratory Study Of Software Reverse Engineering In A Security Context, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois

Research Collection School Of Computing and Information Systems

Illegal cyberspace activities are increasing rapidly and many software engineers are using reverse engineering methods to respond to attacks. The security-sensitive nature of these tasks, such as the understanding of malware or the decryption of encrypted content, brings unique challenges to reverse engineering: work has to be done offline, files can rarely be shared, time pressure is immense, and there is a lack of tool and process support for capturing and sharing the knowledge obtained while trying to understand plain assembly code. To help us gain an understanding of this reverse engineering work, we report on an exploratory study done …

Location-Dependent Spatial Query Containment, Ken C. K. Lee, Brandon Unger, Baihua Zheng, Wang-Chien Lee

Research Collection School Of Computing and Information Systems

Nowadays, location-related information is highly accessible to mobile users via issuing Location-Dependent Spatial Queries (LDSQs) with respect to their locations wirelessly to Location-Based Service (LBS) servers. Due to the limited mobile device battery energy, scarce wireless bandwidth, and heavy LBS server workload, the number of LDSQs submitted over wireless channels to LBS servers for evaluation should be minimized as appropriate. In this paper, we exploit query containment techniques for LDSQs (called LDSQ containment) to enable mobile clients to determine whether the result of a new LDSQ Q′ is completely covered by that of another LDSQ Q previously answered by a …

Concern Localization Using Information Retrieval: An Empirical Study On Linux Kernel, Shaowei Wang, David Lo, Zhenchang Xing, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Many software maintenance activities need to find code units (functions, files, etc.) that implement a certain concern (features, bugs, etc.). To facilitate such activities, many approaches have been proposed to automatically link code units with concerns described in natural languages, which are termed as concern localization and often employ Information Retrieval (IR) techniques. There has not been a study that evaluates and compares the effectiveness of latest IR techniques on a large dataset. This study fills this gap by investigating ten IR techniques, some of which are new and have not been used for concern localization, on a Linux kernel …

Code Search Via Topic-Enriched Dependence Graph Matching, Shaowei Wang, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Source code contains textual, structural, and semantic information, which can all be leveraged for effective search. Some studies have proposed semantic code search where users can specify query topics in a natural language. Other studies can search through system dependence graphs. In this paper, we propose a semantic dependence search engine that integrates both kinds of techniques and can retrieve code snippets based on expressive user queries describing both topics and dependencies. Users can specify their search targets in a free form format describing desired topics (i.e., high-level semantic or functionality of the target code); a specialized graph query language …

Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epinions, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two subcommunities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging …

Direction-Based Surrounder Queries For Mobile Recommendations, Xi Guo, Baihua Zheng, Yoshiharu Ishikawa, Yunjun Gao

Research Collection School Of Computing and Information Systems

Location-based recommendation services recommend objects to the user based on the user’s preferences. In general, the nearest objects are good choices considering their spatial proximity to the user. However, not only the distance of an object to the user but also their directional relationship are important. Motivated by these, we propose a new spatial query, namely a direction-based surrounder (DBS) query, which retrieves the nearest objects around the user from different directions. We define the DBS query not only in a two-dimensional Euclidean space E">EE but also in a road network R">RR . In the Euclidean space E" …

On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu

Research Collection School Of Computing and Information Systems

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative …

Adaptive Collision Resolution For Efficient Rfid Tag Identification, Yung-Chun Chen, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li, Enrico Winata

Research Collection School Of Computing and Information Systems

In large-scale RFID systems, all of the communications between readers and tags are via a shared wireless channel. When a reader intends to collect all IDs from numerous existing tags, a tag identification process is invoked by the reader to collect the tags' IDs. This phenomenon results in tag-to-reader signal collisions which may suppress the system performance greatly. To solve this problem, we design an efficient tag identification protocol in which a significant gain is obtained in terms of both identification delay and communication overhead. A k-ary tree-based abstract is adopted in our proposed tag identification protocol as underlying architecture …

Using Social Annotations For Trend Discovery In Scientific Publications, Meiqun Hu, Ee Peng Lim, Jing Jiang

Research Collection School Of Computing and Information Systems

Social tags and citing documents are two forms of social annotations to scientific publications. These social annotations provide useful contextual and temporal information for the annotated work, which encapsulates the attention and interest of the annotators. In this work, we explore the use of social annotations for discovering trends in scientific publications. We propose a trend discovery process that employs trend estimation and trend selection and ranking for analyzing the emerging trends shown in the social annotation profiles. The proposed sigmoid trend estimator allows us to characterize and compare how much, when and how fast the trends emerge. To perform …

Virality Modeling And Analysis, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Virality is a virus-like behavior that allows a piece of information to widely and quickly diffuse within the network of adopters through word of mouth. It is about how easy users propagate information to their friends and friends of friends by means of diffusion. While virality of information has several interesting applications, there are much research to be conducted on virality. These areas of research include understanding the mechanism of virality, modeling the virality both qualitatively and quantitatively, and applying virality to applications such as marketing, event detection, and others. In this paper, we survey existing works on quantitative models …

Influence Diagrams With Memory States: Representation And Algorithms, Xiaojian Wu, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Influence diagrams (IDs) offer a powerful framework for decision making under uncertainty, but their applicability has been hindered by the exponential growth of runtime and memory usage--largely due to the no-forgetting assumption. We present a novel way to maintain a limited amount of memory to inform each decision and still obtain near-optimal policies. The approach is based on augmenting the graphical model with memory states that represent key aspects of previous observations--a method that has proved useful in POMDP solvers. We also derive an efficient EM-based message-passing algorithm to compute the policy. Experimental results show that this approach produces highquality …

Collaborative Online Learning Of User Generated Content, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi, Wenting Liu, Ramesh Jain

Research Collection School Of Computing and Information Systems

We study the problem of online classification of user generated content, with the goal of efficiently learning to categorize content generated by individual user. This problem is challenging due to several reasons. First, the huge amount of user generated content demands a highly efficient and scalable classification solution. Second, the categories are typically highly imbalanced, i.e., the number of samples from a particular useful class could be far and few between compared to some others (majority class). In some applications like spam detection, identification of the minority class often has significantly greater value than that of the majority class. Last …

An Efficient Algorithm For Learning Event-Recording Automata, Shang-Wei Lin, Étienne André, Jin Song Dong, Jun Sun, Yang Liu

Research Collection School Of Computing and Information Systems

In inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, …

Using Semantic Templates To Study Vulnerabilities Recorded In Large Software Repositories, Yan Wu

Student Work

Software vulnerabilities allow an attacker to reduce a system's Confidentiality, Availability, and Integrity by exposing information, executing malicious code, and undermine system functionalities that contribute to the overall system purpose and need. With new vulnerabilities discovered everyday in a variety of applications and user environments, a systematic study of their characteristics is a subject of immediate need for the following reasons:

• The high rate in which information about past and new vulnerabilities are accumulated makes it difficult to absorb and comprehend.
• Rather than learning from past mistakes, similar types of vulnerabilities are observed repeatedly.
• As the scale and complexity of …

Cooperative Reinforcement Learning In Topology-Based Multi-Agent Systems, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Topology-based multi-agent systems (TMAS), wherein agents interact with one another according to their spatial relationship in a network, are well suited for problems with topological constraints. In a TMAS system, however, each agent may have a different state space, which can be rather large. Consequently, traditional approaches to multi-agent cooperative learning may not be able to scale up with the complexity of the network topology. In this paper, we propose a cooperative learning strategy, under which autonomous agents are assembled in a binary tree formation (BTF). By constraining the interaction between agents, we effectively unify the state space of individual …

Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

An effective relevance feedback solution plays a key role in interactive intelligent 3D object retrieval systems. In this work, we investigate the relevance feedback problem for interactive intelligent 3D object retrieval, with the focus on studying effective machine learning algorithms for improving the user's interaction in the retrieval task. One of the key challenges is to learn appropriate kernel similarity measure between 3D objects through the relevance feedback interaction with users. We address this challenge by presenting a novel framework of Active multiple kernel learning (AMKL), which exploits multiple kernel learning techniques for relevance feedback in interactive 3D object retrieval. …

A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

There has been tremendous interest in diffusion of innovations or information in a social system. Nowadays, social networks (offline as well as online) are considered as important medium for diffusion and large amount of research has been conducted to understand the dynamics of diffusion in social networks. In this work, we review some of the models proposed for diffusion in social networks. We also highlight the major features of these models by dividing the surveyed models into two categories: non-network and network diffusion models. The former refers to user communities without any knowledge about the user relationship network and the …

A Survey Of Techniques And Challenges In Underwater Localization, Hwee-Pink Tan, Roee Diamant, Winston K. G. Seah, Marc Waldmeyer

Research Collection School Of Computing and Information Systems

Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While global positioning system (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit error rate. Moreover, the variable speed …

A Google Earth-Based Framework For Visualization Of The Chesapeake Bay Operational Forecast System, Gary Lawson

Computational Modeling & Simulation Engineering Theses & Dissertations

For the persons who live near and travel the waters of the Chesapeake Bay, the data provided by the Chesapeake Bay Operational Forecast System (CBOFS) is invaluable. The information provided includes measurements and forecasts of surface wind velocity, water current velocity, salinity levels, water level, and temperature. Currently, this information is freely available on the CBQ_FS website hosted by the National Oceanographic and Atmospheric Administration (NOAA). It is offered as Nowcast, measured data, and Forecast data and is visualized using 2D images which describe a subset of the data in an easy to read chart. However, if the data were …