23 Result(s)
within
Conference Paper
Kam-fai Wong
Computer Science
Information Storage and Retrieval
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Chapter and Conference Paper
Rumor Detection with Hierarchical Recurrent Convolutional Neural Network
Automatic rumor detection for events on online social media has attracted considerable attention in recent years. Usually, the events on social media are divided into several time segments, and for each segmen...
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Chapter and Conference Paper
A Tensor Factorization Based User Influence Analysis Method with Clustering and Temporal Constraint
User influence analysis in social media has attracted tremendous interest from both the sociology and social data mining. It is becoming a hot topic recently. However, most approaches ignore the temporal chara...
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Chapter and Conference Paper
The Role of Physical Location in Our Online Social Networks
One of the most important properties of social networking sites is its reachability – no physical location constraint. In addition, all social networking sites allow us to search people with common interests, ...
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Chapter and Conference Paper
Learning to Rank Microblog Posts for Real-Time Ad-Hoc Search
Microblogging websites have emerged to the center of information production and diffusion, on which people can get useful information from other users’ microblog posts. In the era of Big Data, we are overwhelm...
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Chapter and Conference Paper
An Iterative Emotion Classification Approach for Microblogs
The typical emotion classification approach adopts one-step single-label classification using intra-sentence features such as unigrams, bigrams and emotion words. However, single-label classifier with intra-se...
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Chapter and Conference Paper
Recurrent Neural Networks with External Memory for Spoken Language Understanding
Recurrent Neural Networks (RNNs) have become increasingly popular for the task of language understanding. In this task, a semantic tagger is deployed to associate a semantic label to each word in an input sequ...
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Chapter and Conference Paper
Trending Sentiment-Topic Detection on Twitter
Twitter plays a significant role in information diffusion and has evolved to an important information resource as well as news feed. People wonder and care about what is happening on Twitter and what news it i...
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Chapter and Conference Paper
CLUSM: An Unsupervised Model for Microblog Sentiment Analysis Incorporating Link Information
Microblog has become a popular platform for people to share their ideas, information and opinions. In addition to textual content data, social relations and user behaviors in microblog provide us additional li...
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Chapter and Conference Paper
Weight-Based Boosting Model for Cross-Domain Relevance Ranking Adaptation
Adaptation techniques based on importance weighting were shown effective for RankSVM and RankNet, viz., each training instance is assigned a target weight denoting its importance to the target domain and incorpor...
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Chapter and Conference Paper
An Effective Approach for Topic-Specific Opinion Summarization
Topic-specific opinion summarization (TOS) plays an important role in hel** users digest online opinions, which targets to extract a summary of opinion expressions specified by a query, i.e. topic-specific o...
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Chapter and Conference Paper
A Chinese Sentence Compression Method for Opinion Mining
The Chinese sentences in news articles are usually very long, which set up obstacles for further opinion mining steps. Sentence compression is the task of producing a brief summary at the sentence level. Conve...
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Chapter and Conference Paper
Summarizing and Extracting Online Public Opinion from Blog Search Results
As more and more people are willing to publish their attitudes and feelings in blogs, how to provide an efficient way to summarize and extract public opinion in blogosphere has become a major concern for both ...
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Chapter and Conference Paper
Opinion Target Network and Bootstrap** Method for Chinese Opinion Target Extraction
Opinion mining systems suffer a great loss when unknown opinion targets constantly appear in newly composed reviews. Previous opinion target extraction methods typically consider human-compiled opinion targets...
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Chapter and Conference Paper
Joint Ranking for Multilingual Web Search
Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s language. Existing approaches are foc...
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Chapter and Conference Paper
Event-Based Summarization Using Time Features
We investigate whether time features help to improve event-based summarization. In this paper, events are defined as event terms and the associated event elements. While event terms represent the actions thems...
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Chapter and Conference Paper
Fast Structural Join with a Location Function
A structural join evaluates structural relationship (parent-child or ancestor-descendant) between xml elements. It serves as an important computation unit in xml pattern matching, such as twig joins. There exists...
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Chapter and Conference Paper
Natural Document Clustering by Clique Percolation in Random Graphs
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/or the probability distributi...
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Chapter and Conference Paper
Phoneme-Based Transliteration of Foreign Names for OOV Problem
A proper noun dictionary is never complete rendering name translation from English to Chinese ineffective. One way to solve this problem is not to rely on a dictionary alone but to adopt automatic translation ...
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Chapter and Conference Paper
Improving Text Similarity Measurement by Critical Sentence Vector Model
We propose the Critical Sentence Vector Model (CSVM), a novel model to measure text similarity. The CSVM accounts for the structural and semantic information of the document. Compared to existing methods based on...
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Chapter and Conference Paper
Improving Transliteration with Precise Alignment of Phoneme Chunks and Using Contextual Features
Automatic transliteration of foreign names is basically regarded as a diminutive clone of the machine translation (MT) problem. It thus follows IBM’s conventional MT models under the source-channel framework. ...
