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Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin Nov 2012

Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin

Research Collection School Of Computing and Information Systems

This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …

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Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou Nov 2012

Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou

Research Collection School Of Computing and Information Systems

Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in SinaWeibo. Multimedia contents …

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Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang Oct 2012

Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Defects are prevalent in software systems. In order to understand defects better, industry practitioners often categorize bugs into various types. One common kind of categorization is the IBM’s Orthogonal Defect Classification (ODC). ODC proposes various orthogonal classification of defects based on much information about the defects, such as the symptoms and semantics of the defects, the root cause analysis of the defects, and many more. With these category labels, developers can better perform post-mortem analysis to find out what the common characteristics of the defects that plague a particular software project are. Albeit the benefits of having these categories, for …

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Handling Interpretation And Representation In Multilingual Research: A Meta-Study Of Pragmatic Issues Resulting From The Use Of Multiple Languages In A Qualitative Information Systems Research Work, Ilse Baumgartner Oct 2012

Handling Interpretation And Representation In Multilingual Research: A Meta-Study Of Pragmatic Issues Resulting From The Use Of Multiple Languages In A Qualitative Information Systems Research Work, Ilse Baumgartner

Research Collection School Of Computing and Information Systems

Although the number of multilingual qualitative research studies appears to be growing, investigations concerned with methodological issues arising from the use of several languages within a single research are still very scarce. Most of these seem to deal exclusively with issues related to the use of interpreters and translators in qualitative research (e.g., Temple & Edwards, 2002; Temple, Edwards & Alexander, 2006; Edwards, 1998; Temple & Young 2004). Methodological investigations going beyond pure translation dilemmas in qualitative research are, however, almost non-existent. The reason for this seems to be simple: the situation where the researcher possesses mother-tongue fluency in all …

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In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua Sep 2012

In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as …

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Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang Aug 2012

Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Sufficient training examples are essential for effective learning of semantic visual concepts. In practice, however, acquiring noise-free training examples has always been expensive. Recently the rapid popularization of social media websites, such as Flickr, has made it possible to collect training exemplars without human assistance. This paper proposes a novel and efficient approach to collect training samples from the noisily tagged Web images for visual concept learning, where we try to maximize two important criteria, relevancy and coverage, of the automatically generated training sets. For the former, a simple method named semantic field is introduced to handle the imprecise and …

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Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang Aug 2012

Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang

Research Collection School Of Computing and Information Systems

Singapore, a major hub in the Asia Pacific region well known for its multi-racial and multicultural society, is proud to host the 14th International Conference on Electronic Commerce. Singapore Management University (SMU), the School of Information Systems (SIS) and the Living Analytics Research Center (LARC) are also delighted to be able to support the delivery of this event.

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Information-Theoretic Multi-View Domain Adaptation, Pei Yang, Wei Gao, Qi Tan, Kam-Fai Wong Jul 2012

Information-Theoretic Multi-View Domain Adaptation, Pei Yang, Wei Gao, Qi Tan, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

We use multiple views for cross-domain document classification. The main idea is to strengthen the views’ consistency for target data with source training data by identifying the correlations of domain-specific features from different domains. We present an Information-theoretic Multi-view Adaptation Model (IMAM) based on a multi-way clustering scheme, where word and link clusters can draw together seemingly unrelated domain-specific features from both sides and iteratively boost the consistency between document clusterings based on word and link views. Experiments show that IMAM significantly outperforms state-of-the-art baselines.

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Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang Jul 2012

Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang

Research Collection School Of Computing and Information Systems

Pairwise coreference resolution models must merge pairwise coreference decisions to generate final outputs. Traditional merging methods adopt different strategies such as the best first method and enforcing the transitivity constraint, but most of these methods are used independently of the pairwise learning methods as an isolated inference procedure at the end. We propose a joint learning model which combines pairwise classification and mention clustering with Markov logic. Experimental results show that our joint learning system outperforms independent learning systems. Our system gives a better performance than all the learning-based systems from the CoNLL-2011 shared task on the same dataset. Compared …

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Identifying Event-Related Bursts Via Social Media Activities, Xin Zhao, Baihan Shu, Jing Jiang, Yang Song, Hongfei Yan, Xiaoming Li Jul 2012

Identifying Event-Related Bursts Via Social Media Activities, Xin Zhao, Baihan Shu, Jing Jiang, Yang Song, Hongfei Yan, Xiaoming Li

Research Collection School Of Computing and Information Systems

Activities on social media increase at a dramatic rate. When an external event happens, there is a surge in the degree of activities related to the event. These activities may be temporally correlated with one another, but they may also capture different aspects of an event and therefore exhibit different bursty patterns. In this paper, we propose to identify event-related bursts via social media activities. We study how to correlate multiple types of activities to derive a global bursty pattern. To model smoothness of one state sequence, we propose a novel function which can capture the state context. The experiments …

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Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim Jul 2012

Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneousy captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) …

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Identifying Linux Bug Fixing Patches, Yuan Tian, Julia Lawall, David Lo Jun 2012

Identifying Linux Bug Fixing Patches, Yuan Tian, Julia Lawall, David Lo

Research Collection School Of Computing and Information Systems

In the evolution of an operating system there is a continuing tension between the need to develop and test new features, and the need to provide a stable and secure execution environment to users. A compromise, adopted by the developers of the Linux kernel, is to release new versions, including bug fixes and new features, frequently, while maintaining some older “longterm” versions. This strategy raises the problem of how to identify bug fixing patches that are submitted to the current version but should be applied to the longterm versions as well. The current approach is to rely on the individual …

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Improved Duplicate Bug Report Identification, Yuan Tian, Chengnian Sun, David Lo Mar 2012

Improved Duplicate Bug Report Identification, Yuan Tian, Chengnian Sun, David Lo

Research Collection School Of Computing and Information Systems

Bugs are prevalent in software systems. To improve the reliability of software systems, developers often allow end users to provide feedback on bugs that they encounter. Users could perform this by sending a bug report in a bug report management system like Bugzilla. This process however is uncoordinated and distributed, which means that many users could submit bug reports reporting the same problem. These are referred to as duplicate bug reports. The existence of many duplicate bug reports may cause much unnecessary manual efforts as often a triager would need to manually tag bug reports as being duplicates. Recently, there …

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Hierarchical Fuzzy Logic System For Implementing Maintenance Schedules Of Offshore Power Systems, C. S. Chang, Zhaoxia Wang, Fan Yang, W. W. Tan Mar 2012

Hierarchical Fuzzy Logic System For Implementing Maintenance Schedules Of Offshore Power Systems, C. S. Chang, Zhaoxia Wang, Fan Yang, W. W. Tan

Research Collection School Of Computing and Information Systems

Smart grid provides the technology for modernizing electricity delivery systems by using distributed and computer-based remote sensing, control and automation, and two-way communications. Potential benefits of the technology are that the smart grid's central control will now be able to control and operate many remote power plant, optimize the overall asset utilization and operational efficiently. In this paper, we propose an innovative approach for the smart grid to handle uncertainties arising from condition monitoring and maintenance of power plant. The approach uses an adaptive maintenance advisor and a system-maintenance optimizer for designing/implementing optimized condition-based maintenance activities, and collectively handles operational …

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Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu Feb 2012

Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu

Research Collection School Of Computing and Information Systems

As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the suspicion on the existence of such manipulation, the amount of such manipulation is unknown, and deciding which reviews to believe in is largely based on the reader's discretion and intuition. Therefore, the success of the manipulation of reviews by firms in generating sales of products is unknown. In this paper, we …

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Information Extraction From Text, Jing Jiang Jan 2012

Information Extraction From Text, Jing Jiang

Research Collection School Of Computing and Information Systems

Information extraction is the task of finding structured information from unstructured or semi-structured text. It is an important task in text mining and has been extensively studied in various research communities including natural language processing, information retrieval and Web mining. It has a wide range of applications in domains such as biomedical literature mining and business intelligence. Two fundamental tasks of information extraction are named entity recognition and relation extraction. The former refers to finding names of entities such as people, organizations and locations. The latter refers to finding the semantic relations such as FounderOf and HeadquarteredIn between entities. In …

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Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra Jan 2012

Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra

Research Collection School Of Computing and Information Systems

The evolution of human society leads to increased affluence and prosperity of certain populations, sometimes at the expense of well-established markets. Market leaders in products and services tend to be so focused on their current customer base that they are caught off guard with the changes in markets created by the evolution. These changes often go unnoticed until it is too late. The change in customer base often requires the repositioning of products and services through innovations, which address new and emerging markets. Some of these changes could potentially result in tectonic market shifts that force innovation managers to involve …

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Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang Jan 2012

Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang

Research Collection School Of Computing and Information Systems

Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two …

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A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo Jan 2012

A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo

Research Collection School Of Computing and Information Systems

Selecting IT service providers in information systems outsourcing involves both qualitative and quantitative evaluations. This paper proposes an integrated multi-criteria decision-making (MCDM) framework to effectively handle uncertainty and subjectivity in the vendor selection process. The proposed methods apply fuzzy logic approach to integrate qualitative survey data into traditional multi-criteria decision models such as data envelope analysis (DEA), analytical hierarchy process (AHP) methods, and TOPSIS. Based on case studies from Iranian banking industry, we empirically test the proposed framework and show it is superior to existing methods. We demonstrate that the fuzzy logic approach provides a robust analysis for vendor selection …

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Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia Jan 2012

Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia

Research Collection School Of Computing and Information Systems

Query suggestion is an assistive technology mechanism commonly used in search engines to enable a user to formulate their search queries by predicting or completing the next few query words that the user is likely to type. In most implementations, the suggestions are mined from query log and use some simple measure of query similarity such as query frequency or lexicographical matching. In this paper, we propose an alternative method of presenting query suggestions by their thematic topics. Our method adopts a document-centric approach to mine topics in the corpus, and does not require the availability of a query log. …

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Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang Dec 2011

Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang

Research Collection School Of Computing and Information Systems

With the rapid growth of social media, there are plenty of information sources freely available online for use. Nevertheless, how to synchronize and leverage these diverse forms of information for multimedia applications remains a problem yet to be seriously studied. This paper investigates the synchronization of multiple media content in the physical form of hyperlinking them. The ultimate goal is to develop browsing systems that author search results with rich media information mined from various knowledge sources. The authoring enables the vivid visualization and exploration of different information landscapes inherent in search results. Several key techniques are studied in this …

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Discussion Of "Biomedical Ontologies: Toward Scientific Debate", Brochhausen M., Burgun A., Ceusters W., Hasman A., Tze-Yun Leong, Musen M., Oliveira J., Peleg M., Rector A., Schulz S. Dec 2011

Discussion Of "Biomedical Ontologies: Toward Scientific Debate", Brochhausen M., Burgun A., Ceusters W., Hasman A., Tze-Yun Leong, Musen M., Oliveira J., Peleg M., Rector A., Schulz S.

Research Collection School Of Computing and Information Systems

With these comments on the paper “Biomedical Ontologies: Toward scientific debate”, written by Victor Maojo et al., Methods of Information in Medicine wants to stimulate a discussion on advantages and challenges of biomedical ontologies. An international group of experts have been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.

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Beyond Search: Event-Driven Summarization For Web Videos, Richard Hong, Jinhui Tang, Hung-Khoon Tan, Chong-Wah Ngo, Shuicheng Yan, Tat-Seng Chua Nov 2011

Beyond Search: Event-Driven Summarization For Web Videos, Richard Hong, Jinhui Tang, Hung-Khoon Tan, Chong-Wah Ngo, Shuicheng Yan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The explosive growth of Web videos brings out the challenge of how to efficiently browse hundreds or even thousands of videos at a glance. Given an event-driven query, social media Web sites usually return a large number of videos that are diverse and noisy in a ranking list. Exploring such results will be time-consuming and thus degrades user experience. This article presents a novel scheme that is able to summarize the content of video search results by mining and threading "key" shots, such that users can get an overview of main content of these videos at a glance. The proposed …

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Finding Relevant Answers In Software Forums, Swapna Gottopati, David Lo, Jing Jiang Nov 2011

Finding Relevant Answers In Software Forums, Swapna Gottopati, David Lo, Jing Jiang

Research Collection School Of Computing and Information Systems

Online software forums provide a huge amount of valuable content. Developers and users often ask questions and receive answers from such forums. The availability of a vast amount of thread discussions in forums provides ample opportunities for knowledge acquisition and summarization. For a given search query, current search engines use traditional information retrieval approach to extract webpages containing relevant keywords. However, in software forums, often there are many threads containing similar keywords where each thread could contain a lot of posts as many as 1,000 or more. Manually finding relevant answers from these long threads is a painstaking task to …

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Virality Modeling And Analysis, Tuan Anh Hoang, Ee-Peng Lim Oct 2011

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 …

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Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang Jul 2011

Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …

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Unsupervised Information Extraction With Distributional Prior Knowledge, Cane Wing-Ki Leung, Jing Jiang, Kian Ming A. Chai, Hai Leong Chieu, Loo-Nin Teow Jul 2011

Unsupervised Information Extraction With Distributional Prior Knowledge, Cane Wing-Ki Leung, Jing Jiang, Kian Ming A. Chai, Hai Leong Chieu, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

We address the task of automatic discovery of information extraction template from a given text collection. Our approach clusters candidate slot fillers to identify meaningful template slots. We propose a generative model that incorporates distributional prior knowledge to help distribute candidates in a document into appropriate slots. Empirical results suggest that the proposed prior can bring substantial improvements to our task as compared to a K-means baseline and a Gaussian mixture model baseline. Specifically, the proposed prior has shown to be effective when coupled with discriminative features of the candidates.

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Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang Jul 2011

Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper we present a novel approach to entity linking based on a statistical language model-based information retrieval with query expansion. We use both local contexts and global world knowledge to expand query language models. We place a strong emphasis on named entities in the local contexts and explore a positional language model to weigh them differently based on their distances to the query. Our experiments on the TAC-KBP 2010 data show that incorporating such contextual information indeed aids in disambiguating the named entities and consistently improves the entity linking performance. Compared with the official results from KBP 2010 …

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Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang Jul 2011

Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …

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Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong Jul 2011

Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Polarity classification of opinionated sentences with both positive and negative sentiments1 is a key challenge in sentiment analysis. This paper presents a novel unsupervised method for discovering intra-sentence level discourse relations for eliminating polarity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was defined empirically based on Rhetorical Structure Theory (RST). Then, a small set of cuephrase-based patterns were utilized to collect a large number of discourse instances which were later converted to semantic sequential representations (SSRs). Finally, an unsupervised method was adopted to generate, weigh and filter new SSRs without cue phrases for recognizing discourse relations. Experimental …

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