Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (1031)
- Computer Sciences (1030)
- Databases and Information Systems (510)
- Artificial Intelligence and Robotics (316)
- Software Engineering (185)
-
- Graphics and Human Computer Interfaces (150)
- Numerical Analysis and Scientific Computing (142)
- Social and Behavioral Sciences (106)
- Programming Languages and Compilers (103)
- Communication (87)
- Social Media (79)
- Engineering (58)
- Computer Engineering (43)
- Business (30)
- Information Security (30)
- Theory and Algorithms (28)
- Data Storage Systems (25)
- Education (22)
- OS and Networks (18)
- E-Commerce (12)
- Medicine and Health Sciences (11)
- Operations Research, Systems Engineering and Industrial Engineering (11)
- Higher Education (10)
- Arts and Humanities (7)
- Asian Studies (7)
- Digital Communications and Networking (7)
- Health Information Technology (7)
- International and Area Studies (7)
- Educational Assessment, Evaluation, and Research (6)
- Finance and Financial Management (6)
- Keyword
-
- Social media (36)
- Deep learning (25)
- Natural language processing (22)
- Large Language Models (19)
- LLMs (18)
-
- Machine learning (18)
- Large language models (17)
- Twitter (15)
- Sentiment analysis (14)
- Software engineering (13)
- Text mining (13)
- Computational linguistics (11)
- Neural networks (11)
- Natural Language Processing (10)
- Language model (9)
- Data mining (8)
- Deep Learning (8)
- Large Language Model (8)
- Large language model (8)
- Semantics (8)
- Artificial intelligence (7)
- Generative AI (7)
- Information retrieval (7)
- Question answering (7)
- Reinforcement learning (7)
- Transformer (7)
- Clustering (6)
- Graph neural networks (6)
- Multimodal (6)
- Natural language processing systems (6)
- Publication Year
Articles 991 - 1020 of 1047
Full-Text Articles in Entire DC Network
Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei
Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of extracting technical paraphrases from a parallel software corpus, namely, a collection of duplicate bug reports. Paraphrase acquisition is a fundamental task in the emerging area of text mining for software engineering. Existing paraphrase extraction methods are not entirely suitable here due to the noisy nature of bug reports. We propose a number of techniques to address the noisy data problem. The empirical evaluation shows that our method significantly improves an existing method by upto 58%
Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang
Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang
Research Collection School Of Computing and Information Systems
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we propose to use a multi-task learning method coupled with human guidance to address this weakly-supervised relation extraction problem. The proposed framework models the commonality among different relation types through a shared weight vector, enables knowledge learned from …
Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo
Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The massive amount of near-duplicate and duplicate web videos has presented both challenge and opportunity to multimedia computing. On one hand, browsing videos on Internet becomes highly inefficient for the need to repeatedly fast-forward videos of similar content. On the other hand, the tremendous amount of somewhat duplicate content also makes some traditionally difficult vision tasks become simple and easy. For example, annotating pictures can be as simple as recycling the tags of Internet images retrieved from image search engines. Such tasks, of either to eliminate or to recycle near-duplicates, can usually be achieved by the nearest neighbor search of …
Visual Word Proximity And Linguistics For Semantic Video Indexing And Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Visual Word Proximity And Linguistics For Semantic Video Indexing And Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-visual-words (BoW) has recently become a popular representation to describe video and image content. Most existing approaches, nevertheless, neglect inter-word relatedness and measure similarity by bin-to-bin comparison of visual words in histograms. In this paper, we explore the linguistic and ontological aspects of visual words for video analysis. Two approaches, soft-weighting and constraint-based earth mover’s distance (CEMD), are proposed to model different aspects of visual word linguistics and proximity. In soft-weighting, visual words are cleverly weighted such that the linguistic meaning of words is taken into account for bin-to-bin histogram comparison. In CEMD, a cross-bin matching algorithm is formulated such …
A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian
A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian
Research Collection School Of Computing and Information Systems
Unified modeling language (UML) is the standard modeling language for object-oriented system development. Despite its status as a standard, UML has a fuzzy formal specification and a weak theoretical foundation. Semiotics, the study of signs, provides a good theoretical foundation for UML research because graphical notations (or visual signs) of UML are subjected to the principles of signs. In our research, we use semiotics to study the effectiveness of graphical notations in UML. We hypothesized that the use of iconic signs as UML graphical notations leads to representation that is more accurately interpreted and that arouses fewer connotations than the …
Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi
Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi
Research Collection School Of Computing and Information Systems
A key goal of the Semantic Web is to shift social interaction patterns from a producer-centric paradigm to a consumer-centric one. Treating customers as the most valuable assets and making the business models work better for them are at the core of building successful consumer-centric business models. It follows that customizing business processes constitutes a major concern in the realm of a knowledge-pull-based human semantic Web. This paper conceptualizes the customization of service-based business processes leveraging the existing knowledge of Web services and business processes. We represent this conceptualization as a new Extensible Markup Language (XML) markup language Web Ontology …
Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Research Collection School Of Computing and Information Systems
Community Question Answering (QA) portals contain questions and answers contributed by hundreds of millions of users. These databases of questions and answers are of great value if they can be used directly to answer questions from any user. In this research, we address this collaborative QA task by drawing knowledge from the crowds in community QA portals such as Yahoo! Answers. Despite their popularity, it is well known that answers in community QA portals have unequal quality. We therefore propose a quality-aware framework to design methods that select answers from a community QA portal considering answer quality in addition to …
Chaos And Uncertainty, M. Thulasidas
Chaos And Uncertainty, M. Thulasidas
Research Collection School Of Computing and Information Systems
The end of 2008 in the finance industry can be summarized in two words – chaos and uncertainty. The subprime crisis, where everybody lost; the dizzying commodity price movements; the pink slip syndrome; the spectacular bank busts; and the gargantuan bail-outs all vouch for it.
Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a novel approach to exploit the ontological relationship of visual words by linguistic reasoning. A visual word ontology is constructed to facilitate the rigorous evaluation of linguistic similarity across visual words. The linguistic similarity measurement enables cross-bin matching of visual words, compromising the effectiveness and speed of conventional keypoint matching and bag-of-word approaches. A constraint EMD is proposed and experimented to efficiently match visual words. Empirical findings indicate that the proposed approach offers satisfactory performance to near-duplicate retrieval, while still enjoying the merit of speed efficiency compared with other techniques.
Using English Information In Non-English Web Search, Wei Gao, Wei Gao, Ming Zhou
Using English Information In Non-English Web Search, Wei Gao, Wei Gao, Ming Zhou
Research Collection School Of Computing and Information Systems
The leading web search engines have spent a decade building highly specialized ranking functions for English web pages. One of the reasons these ranking functions are effective is that they are designed around features such as PageRank, automatic query and domain taxonomies, and click-through information, etc. Unfortunately, many of these features are absent or altered in other languages. In this work, we show how to exploit these English features for a subset of Chinese queries which we call linguistically non-local (LNL). LNL Chinese queries have a minimally ambiguous English translation which also functions as a good English query. We first …
Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang
Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with ontology knowledge, while emphasizing consistent and uniform comparison of ontological relatedness among concepts for query-to-concept mapping. OS2, in addition to being a linear space like OSS, also guarantees orthogonality of the semantic space. Compared with other ontology reasoning measures, both spaces are capable of providing platforms that offer a global view of concept inter-relatedness, by allowing evaluation of concept similarity …
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …
Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo
Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Event detection plays an essential role in video content analysis. However, the existing features are still weak in event detection because: i) most features just capture what is involved in an event or how the event evolves separately, and thus cannot completely describe the event; ii) to capture event evolution information, only motion distribution over the whole frame is used which proves to be noisy in unconstrained videos; iii) the estimated object motion is usually distorted by camera movement. To cope with these problems, in this paper, we propose a new motion feature, namely Expanded Relative Motion Histogram of Bag-ofVisual-Words …
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing network model for the fusion of multimedia information. By synchronizing the encoding of information across multiple media channels, the neural model known as fusion Adaptive Resonance Theory (fusion ART) generates clusters that encode the associative mappings across multimedia information in a real-time and continuous manner. In addition, by incorporating a semantic category channel, fusion ART further enables multimedia information to be fused into predefined themes or semantic categories. We illustrate the fusion ART’s functionalities through experiments on two multimedia data sets in the terrorist domain and show the viability of the proposed approach.
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Research Collection School Of Computing and Information Systems
While mobile computing provides organizations with many information systems implementation alternatives, it is often difficult to predict the potential benefits, limitations, and problems with mobile applications. Given the inherent portability of mobile devices, many design and use issues can arise which do not exist with desktop systems. While many existing rules of thumb for design of stationary systems apply to mobile systems, many new ones emerge. Issues such as the security and privacy of information take on new dimensions, and potential conflicts can develop when a single mobile device serves both personal and business needs. This paper identifies potential issues …
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Research Collection School Of Computing and Information Systems
Even today, software projects still suffer from delays and budget overspending. The causes for this problem are compounded when the project team is distributed across different locations and generally attributed to the decreasing ability to communicate well (due to cultural, linguistic, and physical distance). Many projects, especially those with off-shoring component, consist of small iterations with changes, deletions and additions, yet there is no formal model of the flow of iterations available. A number of commercially available project prediction tools for projects as a whole exist, but the model adaptation process by iteration, if it exists, is unclear. Furthermore, no …
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
A critical issue of large-scale multimedia retrieval is how to develop an effective framework for ranking the search results. This problem is particularly challenging for content-based video retrieval due to some issues such as short text queries, insufficient sample learning, fusion of multimodal contents, and large-scale learning with huge media data. In this paper, we propose a novel multimodal and multilevel (MMML) ranking framework to attack the challenging ranking problem of content-based video retrieval. We represent the video retrieval task by graphs and suggest a graph based semi-supervised ranking (SSR) scheme, which can learn with small samples effectively and integrate …
A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun
A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun
Research Collection School Of Computing and Information Systems
Semantic Web services have been one of the most significant research areas within the semantic Web vision, and have been recognized as a promising technology that exhibits huge commercial potential. Current semantic Web service research focuses on defining models and languages for the semantic markup of all relevant aspects of services, which are accessible through a Web service interface. The Web service modelling ontology (WSMO) is one of the most significant semantic Web service framework proposed to date. To support the standardization and tool support of WSMO, a formal semantics of the language is highly desirable. As there are a …
How Friendly Is Too Friendly?, M. Thulasidas
How Friendly Is Too Friendly?, M. Thulasidas
Research Collection School Of Computing and Information Systems
Being a boss is tough and being a good boss is a tricky balancing act. One issue many bosses face is: How friendly can they become with their team?
Document Selection For Extracting Entity And Relationship Instances Of Terrorist Events, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Maggy Anastasia Suryanto, Rohan Kumar Gunaratna
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 …
Experimenting Vireo-374: Bag-Of-Visual-Words And Visual-Based Ontology For Semantic Video Indexing And Search, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Feng Wang, Wanlei Zhao, Hung-Khoon Tan, Xiao Wu
Experimenting Vireo-374: Bag-Of-Visual-Words And Visual-Based Ontology For Semantic Video Indexing And Search, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Feng Wang, Wanlei Zhao, Hung-Khoon Tan, Xiao Wu
Research Collection School Of Computing and Information Systems
In this paper, we present our approaches and results of high-level feature extraction and automatic video search in TRECVID-2007.
Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for …
Deception In Cyberspace: A Comparison Of Text-Only Vs. Avatar-Supported Medium, Holtjona Galanxhi, Fiona Fui-Hoon Nah
Deception In Cyberspace: A Comparison Of Text-Only Vs. Avatar-Supported Medium, Holtjona Galanxhi, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
The use of anthropomorphic avatars provides Internet users the opportunity and freedom to manipulate their identity. As cyberspace becomes a haven for deceptive behavior, human–computer interaction research will need to be carried out to study and understand these deceptive behaviors. The objective of this research is to investigate the behavior of deceivers and non-deceivers (or truth-tellers) in the cyberspace environment. We examine if the intention to deceive others influences one's choice of avatars in the online chat environment. We also investigate if communication medium (text-only vs. avatar-supported chat) influences one's perception of trustworthiness of the communication partner. A lab experiment …
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
Research Collection School Of Computing and Information Systems
Grammar checking and correction comprise of the primary problems in the area of Natural Language Processing (NLP). Traditional approaches fall into two major categories: Rule based and Corpus based. While the former relies heavily on grammar rules the latter approach is statistical in nature. We provide a novel corpus based approach for grammar checking that uses the principles of an Artificial Immune System (AIS).We treat grammatical error as pathogens (in immunological terms) and build antibody detectors capable of detecting grammatical errors while allowing correct constructs to filter through. Our results show that it is possible to detect a range of …
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Research Collection School Of Computing and Information Systems
Query suggestion aims to suggest relevant queries for a given query, which help users better specify their information needs. Previously, the suggested terms are mostly in the same language of the input query. In this paper, we extend it to cross-lingual query suggestion (CLQS): for a query in one language, we suggest similar or relevant queries in other languages. This is very important to scenarios of cross-language information retrieval (CLIR) and cross-lingual keyword bidding for search engine advertisement. Instead of relying on existing query translation technologies for CLQS, we present an effective means to map the input query of one …
Instance Weighting For Domain Adaptation In Nlp, Jing Jiang, Chengxiang Zhai
Instance Weighting For Domain Adaptation In Nlp, Jing Jiang, Chengxiang Zhai
Research Collection School Of Computing and Information Systems
Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation problem from the instance weighting per- spective. We formally analyze and charac- terize the domain adaptation problem from a distributional view, and show that there are two distinct needs for adaptation, cor- responding to the different distributions of instances and classification functions in the source and the target domains. We then propose a general instance weighting frame- work for domain adaptation. Our empir- ical results on three NLP tasks show that …
Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan
Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan
Research Collection School Of Computing and Information Systems
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a supervised learning setting, we investigate the use of random forest for automatic e-mail filing into folders and spam e-mail filtering. We show that random forest is a good choice for these tasks as it runs fast on large and high dimensional databases, is easy to tune and is highly accurate, outperforming popular algorithms such as decision trees, support vector machines and naive Bayes. We introduce a new accurate feature selector with linear time complexity. …
Anticipatory Event Detection Via Classification, He Qi, Kuiyu Chang, Ee Peng Lim
Anticipatory Event Detection Via Classification, He Qi, Kuiyu Chang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airline disasters, etc. In this paper, we describe a new problem, called anticipatory event detection (AED), which aims to detect if a user-specified event has transpired. AED can be viewed as a personalized combination of event tracking and new event detection. We propose using sentence-level and document-level classification approaches to solve the AED problem for …
Businessfinder: Harnessing Presence To Enable Live Yellow Pages For Small, Medium And Micro Mobile Businesses, D. Chakraborty, K. Dasgupta, S. Mittal, Archan Misra, C. Oberle, A. Gupta, E. Newmark
Businessfinder: Harnessing Presence To Enable Live Yellow Pages For Small, Medium And Micro Mobile Businesses, D. Chakraborty, K. Dasgupta, S. Mittal, Archan Misra, C. Oberle, A. Gupta, E. Newmark
Research Collection School Of Computing and Information Systems
Applications leveraging network presence in next-generation cellular networks have so far focused on subscription queries, where "presence" information is extracted from specific devices and sent to entities who have subscribed to such presence information. In this article we present BusinessFinder, a service that leverages the underlying cellular presence substrate to provide efficient, on-demand, context-aware matching of customer requests to nomadic micro businesses as well as small and medium businesses having a mobile workforce. Presence, in the context of BusinessFinder, is not simply limited to phone location and device status, but also encompasses dynamic attributes of vendors (both "mobile" and "static"), …
Discovering Image-Text Associations For Cross-Media Web Information Fusion, Tao Jiang, Ah-Hwee Tan
Discovering Image-Text Associations For Cross-Media Web Information Fusion, Tao Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The diverse and distributed nature of the information published on the World Wide Web has made it difficult to collate and track information related to specific topics. Whereas most existing work on web information fusion has focused on multiple document summarization, this paper presents a novel approach for discovering associations between images and text segments, which subsequently can be used to support cross-media web content summarization. Specifically, we employ a similarity-based multilingual retrieval model and adopt a vague transformation technique for measuring the information similarity between visual features and textual features. The experimental results on a terrorist domain document set …