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Articles 841 - 870 of 1060

Full-Text Articles in Numerical Analysis and Scientific Computing

Event Detection With Common User Interests, Meishan Hu, Aixin Sun, Ee Peng Lim Oct 2008

Event Detection With Common User Interests, Meishan Hu, Aixin Sun, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we aim at detecting events of common user interests from huge volume of user-generated content. The degree of interest from common users in an event is evidenced by a significant surge of event-related queries issued to search for documents (e.g., news articles, blog posts) relevant to the event. Taking the stream of queries from users and the stream of documents as input, our proposed framework seamlessly integrates the two streams into a single stream of query profiles. A query profile is a set of documents matching a query at a given time. With the single stream of …

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Comparison Of Online Social Relations In Volume Vs Interaction: A Case Study Of Cyworld, Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong. Jeong Oct 2008

Comparison Of Online Social Relations In Volume Vs Interaction: A Case Study Of Cyworld, Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong. Jeong

Research Collection School Of Computing and Information Systems

Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction.Does the interaction …

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Determining The Number Of Bp Neural Network Hidden Layer Units, Huayu Shen, Zhaoxia Wang, Chengyao Gao, Juan Qin, Fubin Yao, Wei Xu Oct 2008

Determining The Number Of Bp Neural Network Hidden Layer Units, Huayu Shen, Zhaoxia Wang, Chengyao Gao, Juan Qin, Fubin Yao, Wei Xu

Research Collection School Of Computing and Information Systems

This paper proposed an improved method to contrapose the problem which is difficult to determine the number of BP neural network hidden layer units. it is proved that the method is efficeient in reducing the frequency of the test through experients, and improves the efficiency of determining the best number of hidden units, which is more valuable in the applications.

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Spatio-Temporal Efficiency In A Taxi Dispatch System, Darshan Santani, Rajesh Krishna Balan, C. Jason Woodard Oct 2008

Spatio-Temporal Efficiency In A Taxi Dispatch System, Darshan Santani, Rajesh Krishna Balan, C. Jason Woodard

Research Collection School Of Computing and Information Systems

In this paper, we present an empirical analysis of the GPS-enabled taxi dispatch system used by the world’s second largest land transportation company. We first summarize the collective dynamics of the more than 6,000 taxicabs in this fleet. Next, we propose a simple method for evaluating the efficiency of the system over a given period of time and geographic zone. Our method yields valuable insights into system performance—in particular, revealing significant inefficiencies that should command the attention of the fleet operator. For example, despite the state of the art dispatching system employed by the company, we find imbalances in supply …

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Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han Aug 2008

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 …

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Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis Aug 2008

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 …

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A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang Aug 2008

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 …

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Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou Jul 2008

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 …

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Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim Jul 2008

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 …

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Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim Jul 2008

Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim

Research Collection School Of Computing and Information Systems

Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.

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Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee Jul 2008

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, …

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Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen Jun 2008

Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen

Research Collection School Of Computing and Information Systems

To generate a believable and dynamic virtual world is a great challenge in interactive storytelling. In this paper, we propose a model, namely evolutionary fuzzy cognitive map (E-FCM), to model the dynamic causal relationships among different context variables. As an extension to conventional FCM, E-FCM models not only the fuzzy causal relationships among the variables, but also the probabilistic property of causal relationships, and asynchronous activity update of the concepts. With this model, the context variables evolve in a dynamic and uncertain manner with the according evolving time. As a result, the virtual world is presented more realistically and dynamically.

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Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta Jun 2008

Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta

Research Collection School Of Computing and Information Systems

When multiple users with diverse backgrounds and beliefs edit Wikipedia together, disputes often arise due to disagreements among the users. In this paper, we introduce a novel visualization tool known as WikiNetViz to visualize and analyze disputes among users in a dispute-induced social network. WikiNetViz is designed to quantify the degree of dispute between a pair of users using the article history. Each user (and article) is also assigned a controversy score by our proposed controversy rank model so as to measure the degree of controversy of a user (and an article) by the amount of disputes between the user …

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Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim Jun 2008

Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim

Research Collection School Of Computing and Information Systems

Trust between a pair of users is an important piece of information for users in an online community (such as electronic commerce websites and product review websites) where users may rely on trust information to make decisions. In this paper, we address the problem of predicting whether a user trusts another user. Most prior work infers unknown trust ratings from known trust ratings. The effectiveness of this approach depends on the connectivity of the known web of trust and can be quite poor when the connectivity is very sparse which is often the case in an online community. In this …

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Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang Jun 2008

Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant to a given information seeking task. In this paper, we introduce a visual analytics tool called ER-Explorer to support such an analysis task. ER-Explorer consists of a data model known as TUBE and a set of data manipulation operations specially designed for examining entities and relationships in text. As part of TUBE, a set of interestingness measures is defined to help exploring entities and their relationships. We illustrate the use of ER-Explorer …

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Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis Jun 2008

Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q 2 Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M Q × P such that (i) each point q 2 Q (p 2 P) appears at most k times (at most nce) in M, (ii) the size of M is maximized (i.e., it comprises min{|P|,P q2Q q.k} pairs), and (iii) the total assignment cost (i.e., the sum of Euclidean distances within all pairs) is minimized. Thus, the CCA problem is …

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Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan May 2008

Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan

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 servers over extended periods of time. A breached server that is not detected in time may return incorrect query answers to users. In this article, we introduce authentication schemes for users to verify that their query answers from an online server are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values are legitimate). We introduce a scheme that supports range selection, projection as well as primary key-foreign key join queries on relational databases. We also …

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Building A Web Of Trust Without Explicit Trust Ratings, Young Ae Kim, Minh-Tam Le, Hady W. Lauw, Ee Peng Lim, Haifeng Liu, Jaideep Srivastava Apr 2008

Building A Web Of Trust Without Explicit Trust Ratings, Young Ae Kim, Minh-Tam Le, Hady W. Lauw, Ee Peng Lim, Haifeng Liu, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

A satisfactory and robust trust model is gaining importance in addressing information overload, and helping users collect reliable information in online communities. Current research on trust prediction strongly relies on a web of trust, which is directly collected from users based on previous experience. However, the web of trust is not always available in online communities and even though it is available, it is often too sparse to predict the trust value between two unacquainted people with high accuracy. In this paper, we propose a framework to derive degree of trust based on users' expertise and users' affinity for certain …

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Processing Transitive Nearest-Neighbor Queries In Multi-Channel Access Environments, Xiao Zhang, Wang-Chien Lee, Prasnjit Mitra, Baihua Zheng Mar 2008

Processing Transitive Nearest-Neighbor Queries In Multi-Channel Access Environments, Xiao Zhang, Wang-Chien Lee, Prasnjit Mitra, Baihua Zheng

Research Collection School Of Computing and Information Systems

Wireless broadcast is an efficient way for information dissemination due to its good scalability [10]. Existing works typically assume mobile devices, such as cell phones and PDAs, can access only one channel at a time. In this paper, we consider a scenario of near future where a mobile device has the ability to process queries using information simultaneously received from multiple channels. We focus on the query processing of the transitive nearest neighbor (TNN) search [19]. Two TNN algorithms developed for a single broadcast channel environment are adapted to our new broadcast enviroment. Based on the obtained insights, we propose …

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On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang Feb 2008

On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang

Research Collection School Of Computing and Information Systems

Wikipedia 1 is a very large and successful Web 2.0 example. As the number of Wikipedia articles and contributors grows at a very fast pace, there are also increasing disputes occurring among the contributors. Disputes often happen in articles with controversial content. They also occur frequently among contributors who are "aggressive" or controversial in their personalities. In this paper, we aim to identify controversial articles in Wikipedia. We propose three models, namely the Basic model and two Controversy Rank (CR) models. These models draw clues from collaboration and edit history instead of interpreting the actual articles or edited content. While …

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Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston Jan 2008

Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

This paper discusses the importance of and a solution to separating the information flow from the physical product flow in a supply chain. Motivated by the inefficient demand forecast caused by information asymmetry and lack of an incentive among supply chain partners to share valuable information, we propose a radically new framework called collective outsourcing to market (COM) to address many information supply chain design challenges. To validate the COM framework, we consider a supply chain with one manufacturer and multiple downstream retailers. Retailers privately acquire demand forecast information that they do not have incentive to share horizontally with other …

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Document Selection For Extracting Entity And Relationship Instances Of Terrorist Events, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Maggy Anastasia Suryanto, Rohan Kumar Gunaratna Jan 2008

Document Selection For Extracting Entity And Relationship Instances Of Terrorist Events, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Maggy Anastasia Suryanto, Rohan Kumar Gunaratna

Research Collection School Of Computing and Information Systems

In this chapter, we study the problem of selecting documents so as to extract terrorist event information from a collection of documents. We represent an event by its entity and relation instances. Very often, these entity and relation instances have to be extracted from multiple documents. We therefore define an information extraction (IE) task as selecting documents and extracting from which entity and relation instances relevant to a user-specified event (aka domain specific event entity and relation extraction). We adopt domain specific IE patterns to extract potentially relevant entity and relation instances from documents, and develop a number of document …

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Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias Dec 2007

Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias

Research Collection School Of Computing and Information Systems

The increasing trend of embedding positioning capabilities (for example, GPS) in mobile devices facilitates the widespread use of location-based services. For such applications to succeed, privacy and confidentiality are essential. Existing privacy-enhancing techniques rely on encryption to safeguard communication channels, and on pseudonyms to protect user identities. Nevertheless, the query contents may disclose the physical location of the user. In this paper, we present a framework for preventing location-based identity inference of users who issue spatial queries to location-based services. We propose transformations based on the well-established K-anonymity concept to compute exact answers for range and nearest neighbor search, without …

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On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong Nov 2007

On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong

Research Collection School Of Computing and Information Systems

Wikipedia is presently the largest free-and-open online encyclopedia collaboratively edited and maintained by volunteers. While Wikipedia offers full-text search to its users, the accuracy of its relevance-based search can be compromised by poor quality articles edited by non-experts and inexperienced contributors. In this paper, we propose a framework that re-ranks Wikipedia search results considering article quality. We develop two quality measurement models, namely Basic and PeerReview, to derive article quality based on co-authoring data gathered from articles' edit history. Compared with Wikipedia's full-text search engine, Google and Wikiseek, our experimental results showed that (i) quality-only ranking produced by PeerReview gives …

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Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun Nov 2007

Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun

Research Collection School Of Computing and Information Systems

Much existing research on blogs focused on posts only, ignoring their comments. Our user study conducted on summarizing blog posts, however, showed that reading comments does change one's understanding about blog posts. In this research, we aim to extract representative sentences from a blog post that best represent the topics discussed among its comments. The proposed solution first derives representative words from comments and then selects sentences containing representative words. The representativeness of words is measured using ReQuT (i.e., Reader, Quotation, and Topic). Evaluated on human labeled sentences, ReQuT together with summation-based sentence selection showed promising results.

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Measuring Article Quality In Wikipedia: Models And Evaluation, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady W. Lauw, Ba-Quy Vuong Nov 2007

Measuring Article Quality In Wikipedia: Models And Evaluation, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady W. Lauw, Ba-Quy Vuong

Research Collection School Of Computing and Information Systems

Wikipedia has grown to be the world largest and busiest free encyclopedia, in which articles are collaboratively written and maintained by volunteers online. Despite its success as a means of knowledge sharing and collaboration, the public has never stopped criticizing the quality of Wikipedia articles edited by non-experts and inexperienced contributors. In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia. We propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history. Our Basic model is designed based …

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Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang Nov 2007

Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

Searching answers to complex questions is a challenging IR task. In this paper, we examine the use of query templates with semantic slots to formulate slot-based queries. These queries have query terms assigned to entity and relationship slots. We develop several query expansion methods for slot-based queries so as to improve their retrieval effectiveness on a document collection. Each method consists of a combination of term scoring scheme, term scoring formula, and term assignment scheme. Our preliminary experiments evaluate these different slot-based query expansion methods on a collection of news documents,and conclude that:(1) slot-based queries yield better retrieval accuracy compared …

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A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim Oct 2007

A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.

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Option-Based Risk Management: A Field Study Of Sequential Information Technology Investment Decisions, Michel Benaroch, Mark Jeffery, Robert John Kauffman, Sandeep Shah Oct 2007

Option-Based Risk Management: A Field Study Of Sequential Information Technology Investment Decisions, Michel Benaroch, Mark Jeffery, Robert John Kauffman, Sandeep Shah

Research Collection School Of Computing and Information Systems

This field study research evaluates the viability of applying an option-based risk management (OBRiM) framework, and its accompanying theoretical perspective and methodology, to real-world sequential information technology (IT) investment problems. These problems involve alternative investment structures that bear different risk profiles for the firm, and also may improve the payoffs of the associated projects and the organization's performance. We sought to surface the costs, benefits, and risks associated with a complex sequential investment setting that has the key features that OBRiM treats. We combine traditional, purchased real options that subsequently create strategic flexibility for the decision maker, with implicit or …

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Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han Oct 2007

Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han

Research Collection School Of Computing and Information Systems

Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, demanding powerful data mining methods. Due to inherent noise or data diversity, it is crucial to address the issue of approximation, if one wants to mine patterns that are potentially interesting with tolerable variations. In this paper, we investigate the problem of mining frequent approximate patterns from a massive network and propose a method called gApprox. gApprox not only finds approximate network patterns, which is the key for many knowledge discovery applications on …

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