Intent-Based User Segmentation With Query Enhancement,
2014
New Jersey Institute of Technology
Intent-Based User Segmentation With Query Enhancement, Wei Xiong
Dissertations
With the rapid advancement of the internet, accurate prediction of user's online intent underlying their search queries has received increasing attention from the online advertising community. As a rich source of information on web user's behavior, query logs have been leveraged by advertising companies to deliver personalized advertisements. However, a typical query usually contains very few terms, which only carry a small amount of information about a user's interest. The tendency of users to use short and ambiguous queries makes it difficult to fully describe and distinguish a user's intent. In addition, the query feature space is sparse, as only …
Implementation Of A Segmented, Transactional Database Caching System,
2014
Minnesota State University, Mankato
Implementation Of A Segmented, Transactional Database Caching System, Benjamin J. Sandmann
Journal of Undergraduate Research at Minnesota State University, Mankato
Research on algorithms and concepts regarding memory-based data caching can help solve the performance bottleneck in current Database Management Systems. Problems such as data concurrency, persistent storage, and transaction management have limited most memory cache’s capabilities. It has also been tough to develop a proper user- oriented and business friendly way of implementing such a system. The research of this project focused on code implementation, abstract methodologies and how to best prepare such an application for common business usage.
An Automatic Dialog System For Student Advising,
2014
Minnesota State University, Mankato
An Automatic Dialog System For Student Advising, Brian Mcmahan
Journal of Undergraduate Research at Minnesota State University, Mankato
Automatic dialog systems are an implementation of natural language processing theory with the goal of allowing the use of natural sentences to communicate with a computer system. The general purpose of this project was to design and implement an automatic dialog system for augmenting university student advising. Student advising is a relatively narrow domain of possible questions and responses. The automatic dialog system focused on prescriptive advising rather than developmental advising to further narrow the domain to scheduling and registration matters. A student advisor was interviewed and recorded during a mock advising session in order to model the interaction between …
Document Retrieval Using Predication Similarity,
2014
Wright State University - Main Campus
Document Retrieval Using Predication Similarity, Kalpa Gunaratna
Kno.e.sis Publications
Document retrieval has been an important research problem over many years in the information retrieval community. State-of-the-art techniques utilize various methods in matching documents to a given document including keywords, phrases, and annotations. In this paper, we propose a new approach for document retrieval that utilizes predications (subject-predicate-object triples) extracted from the documents. We represent documents as sets of predications. We measure the similarity between predications to compute the similarity between documents. Our approach utilizes the hierarchical information available in ontologies in computing concept-concept similarity, making the approach flexible. Predication-based document similarity is more precise and forms the basis for …
Reconstructing A Large-Scale Attribute-Based Social Network,
2014
University of Illinois at Urbana-Champaign
Reconstructing A Large-Scale Attribute-Based Social Network, Weijia Luo, Mario Ventresca
The Summer Undergraduate Research Fellowship (SURF) Symposium
An epidemic occurs when a disease rapidly infects substantially more people than expected compared to past experience of similar diseases. If an epidemic is not contained, it could turn into a pandemic, which will cause a worldwide crisis. Therefore, it is critical to determine and implement epidemic policies that are promising and effective within a short period of time. In this paper, we will develop tools that will allow us to recreate large-scale real-world social networks. Using such networks will enable us to simulate disease spread and determine critical personal and social factors that will be the key to containing …
A Novel Web-Based Depth Video Rewind Approach Toward Fall Preventive Interventions In Hospitals,
2014
Wright State University - Main Campus
A Novel Web-Based Depth Video Rewind Approach Toward Fall Preventive Interventions In Hospitals, Moein Enayati, Tanvi Banerjee, Mihail Popescu, Marjorie Skubic, Marilyn J. Rantz
Kno.e.sis Publications
Falls in the hospital rooms are considered a huge burden on healthcare costs. They can lead to injuries, extended length of stay, and increase in cost for both the patients and the hospital. It can also lead to emotional trauma for the patients and their families [1]. Having Microsoft Kinects installed in the hospital rooms to capture and process every movement in the room, we deployed our previously developed fall-detection system to detect naturally occurring falls, generate a real-time fall alarm and broadcast it to hospital nurses for immediate intervention. These systems also store a processed and reduced version …
Opinion Mining Of Sociopolitical Comments From Social Media,
2014
Singapore Management University
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Dissertations and Theses Collection (Open Access)
Opinions are central to almost all human activities by influencing greatly the decision making process. In this thesis, we present the problems of mining issues, extracting entities and suggestive opinions towards the entities, detecting thoughtful comments, and extracting stances and ideological expressions from online comments in the sociopolitical domain. This study is essential for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Much work has been done to try to uncover consumer sentiments from online comments to help businesses improve their products and services. However, sociopolitical opinion mining poses new challenges due to complex …
Direct Neighbor Search,
2014
Singapore Management University
Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …
Semantic Visualization For Spherical Representation,
2014
Singapore Management University
Semantic Visualization For Spherical Representation, Tuan M. V. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Visualization of high-dimensional data such as text documents is widely applicable. The traditional means is to find an appropriate embedding of the high-dimensional representation in a low-dimensional visualizable space. As topic modeling is a useful form of dimensionality reduction that preserves the semantics in documents, recent approaches aim for a visualization that is consistent with both the original word space, as well as the semantic topic space. In this paper, we address the semantic visualization problem. Given a corpus of documents, the objective is to simultaneously learn the topic distributions as well as the visualization coordinates of documents. We propose …
Utilizing Microblogs For Improving Automatic News High-Lights Extraction,
2014
Singapore Management University
Utilizing Microblogs For Improving Automatic News High-Lights Extraction, Zhongyu Wei, Wei Gao
Research Collection School Of Computing and Information Systems
Story highlights form a succinct single-document summary consisting of 3-4 highlight sentences that reflect the gist of a news article. Automatically producing news highlights is very challenging. We propose a novel method to improve news highlights extraction by using microblogs. The hypothesis is that microblog posts, although noisy, are not only indicative of important pieces of information in the news story, but also inherently “short and sweet” resulting from the artificial compression effect due to the length limit. Given a news article, we formulate the problem as two rank-then-extract tasks: (1) we find a set of indicative tweets and use …
Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning,
2014
Singapore Management University
Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
This work addresses the coordination issue in distributed optimization problem (DOP) where multiple distinct and time-critical tasks are performed to satisfy a global objective function. The performance of these tasks has to be coordinated due to the sharing of consumable resources and the dependency on non-consumable resources. Knowing that it can be sub-optimal to predefine the performance of the tasks for large DOPs, the multi-agent reinforcement learning (MARL) framework is adopted wherein an agent is used to learn the performance of each distinct task using reinforcement learning. To coordinate MARL, we propose a novel coordination strategy integrating Motivated Learning (ML) …
Collaborative Online Multitask Learning,
2014
Nanyang Technological University
Collaborative Online Multitask Learning, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang, Wenting Liu, Ramesh Jain
Research Collection School Of Computing and Information Systems
We study the problem of online multitask learning for solving multiple related classification tasks in parallel, aiming at classifying every sequence of data received by each task accurately and efficiently. One practical example of online multitask learning is the micro-blog sentiment detection on a group of users, which classifies micro-blog posts generated by each user into emotional or non-emotional categories. This particular online learning task is challenging for a number of reasons. First of all, to meet the critical requirements of online applications, a highly efficient and scalable classification solution that can make immediate predictions with low learning cost is …
Online Multiple Kernel Regression,
2014
Singapore Management University
Online Multiple Kernel Regression, Doyen Sahoo, Steven C. H. Hoi, Bin Li
Research Collection School Of Computing and Information Systems
Kernel-based regression represents an important family of learning techniques for solving challenging regression tasks with non-linear patterns. Despite being studied extensively, most of the existing work suffers from two major drawbacks: (i) they are often designed for solving regression tasks in a batch learning setting, making them not only computationally inefficient and but also poorly scalable in real-world applications where data arrives sequentially; and (ii) they usually assume a fixed kernel function is given prior to the learning task, which could result in poor performance if the chosen kernel is inappropriate. To overcome these drawbacks, this paper presents a novel …
Generating Supplementary Travel Guides From Social Media,
2014
Peking University
Generating Supplementary Travel Guides From Social Media, Liu Yang, Jing Jiang, Lifu Huang, Minghui Qiu, Lizi Liao
Research Collection School Of Computing and Information Systems
In this paper we study how to summarize travel-related information in forum threads to generate supplementary travel guides. Such summaries presumably can provide additional and more up-to-date information to tourists. Existing multi-document summarization methods have limitations for this task because (1) they do not generate structured summaries but travel guides usually follow a certain template, and (2) they do not put emphasis on named entities but travel guides often recommend points of interest to travelers. To overcome these limitations, we propose to use a latent variable model to align forum threads with the section structure of well-written travel guides. The …
Jointly Modeling Aspects, Ratings And Sentiments For Movie Recommendation (Jmars),
2014
Singapore Management University
Jointly Modeling Aspects, Ratings And Sentiments For Movie Recommendation (Jmars), Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J. Smola, Jing Jiang, Chong Wang
Research Collection School Of Computing and Information Systems
Recommendation and review sites offer a wealth of information beyond ratings. For instance, on IMDb users leave reviews, commenting on different aspects of a movie (e.g. actors, plot, visual effects), and expressing their sentiments (positive or negative) on these aspects in their reviews. This suggests that uncovering aspects and sentiments will allow us to gain a better understanding of users, movies, and the process involved in generating ratings. The ability to answer questions such as “Does this user care more about the plot or about the special effects?” or ”What is the quality of the movie in terms of acting?” …
Gta-M: Greedy Trajectory-Aware (M Copies) Routing For Airborne Networks,
2014
Institute for Infocomm Research
Gta-M: Greedy Trajectory-Aware (M Copies) Routing For Airborne Networks, Xiaoping Ma, Hwee Xian Tan, Alvin C. Valera
Research Collection School Of Computing and Information Systems
Airborne networks have potential applications in both civilian and military domains - such as passenger in-flight Internet connectivity, air traffic control and in intelligence, surveillance and reconnaissance (ISR) activities. However, airborne networks suffer from frequent disruptions due to high node mobility, ad hoc connectivity and line-of-sight blockages. These challenges can be alleviated through the use of disruption-tolerant networking (DTN) techniques. In this paper, we propose GTA-m, a multi-copy greedy trajectory-aware routing protocol for airborne networks. GTA-m employs DTN capabilities and exploits the use of flight information to forwarded bundles greedily to intended destination(s). To alleviate the local minima issues that …
On Macro And Micro Exploration Of Hashtag Diffusion In Twitter,
2014
Singapore Management University
On Macro And Micro Exploration Of Hashtag Diffusion In Twitter, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
This exploratory work studies hashtag diffusion in Twitter. The analysis is conducted from two aspects. From the macro perspective, we study general properties of hashtag diffusion, and classify hashtags into three main classes based on their temporal dynamics referred as 'single spike', 'multi-spikes', and 'fluctuation', and find that each of these classes has some unique characteristics. From the micro perspective, we investigate individual diffusion.We adopt Edelman's 'topology of influence' theory to identify four type of users with different influence levels in diffusion based on their dynamic retweet behaviors. The results of our study are useful for gaining more insights of …
Diversified Social Influence Maximization,
2014
University of Science and Technology of China
Diversified Social Influence Maximization, Fangshuang Tang, Qi Liu, Hengshu Zhu, Enhong Chen, Feida Zhu
Research Collection School Of Computing and Information Systems
For better viral marketing, there has been a lot of research on social influence maximization. However, the problem that who is influenced and how diverse the influenced population is, which is important in real-world marketing, has largely been neglected. To that end, in this paper, we propose to consider the magnitude of influence and the diversity of the influenced crowd simultaneously. Specifically, we formulate it as an optimization problem, i.e., diversified social influence maximization. First, we present a general framework for this problem, under which we construct a class of diversity measures to quantify the diversity of the influenced crowd. …
Urban Planning Process: Can Technology Enhance Participatory Communication?,
2014
Singapore Management University
Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang
Research Collection School Of Computing and Information Systems
Oftentimes, within the urban planning process, urban planners and GIS experts must work together using desktop Computer-Aided Design (CAD) and Geographic Information System (GIS). However, participatory communication and visualization which are important in the urban planning process, are not a central focus in the design of current computer-aided planning technologies. This study tends to provide an understanding of technological challenges and complexities urban planners and GIS experts encounter while engaging in a participatory environment during the urban planning process. This study also explores the perceptions of urban planners and GIS experts about the potential impact and usefulness of interactive surfaces …
Guest Editorial: Special Issue On Brain Inspired Models Of Cognitive Memory,
2014
Singapore Management University
Guest Editorial: Special Issue On Brain Inspired Models Of Cognitive Memory, Huajin Tang, Kiruthika Ramanathan, Ning Nign
Research Collection School Of Computing and Information Systems
Current memory technologies have experienced significant progress in terms of storage capacity, operation speed, integration capability, etc. However, their functions are highly constrained in storing and transferring data in space and time, prompting the need for improvement. In contrast to physical memories, the biological counterpart – cognitive memory – has versatile functions. For instance, human memory stores data associatively such that different modalities of data could be retrieved simultaneously; it can learn different concepts, categorize and store them in an organized manner; it can process and store data concurrently and in a distributed fashion; it can restore content even if …
