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Community question answering (cQA) has become an important issue due to the popularity of cQA archives on the web. This paper is concerned with the problem of question retrieval. Question retrieval in cQA archives aims to find the existing questions that are semantically equivalent or relevant to the queried questions. However, the lexical gap problem(More)
We demonstrate an optical transmitter based on dynamic optical arbitrary waveform generation (OAWG) which is capable of creating high-bandwidth (THz) data waveforms in any modulation format using the parallel synthesis of multiple coherent spectral slices. As an initial demonstration, the transmitter uses only 5.5 GHz of electrical bandwidth and two(More)
Arsenic levels and speciation in the total suspended particles (TSPs) were quantitatively determined by high performance liquid chromatography on-line coupled with hydride generation atomic fluorescence spectrometry in Beijing, China from February 2009 to March 2011. The high TSP levels fluctuated between 0.07 and 0.79 mg m(-3), with a mean level of 0.32 ±(More)
OBJECT Studies have suggested that depression was accompanied by oxidative stress dysregulation, including abnormal total antioxidant capacity (TAC), antioxidants, free radicals, oxidative damage and autoimmune response products. This meta-analysis aims to analyse the clinical data quantitatively by comparing the oxidative stress markers between depressed(More)
Automatic summarization is an important research issue in natural language processing. This paper presents a special summarization method to generate single-document summary with maximum topic completeness and minimum redundancy. It initially implements the semantic-class-based vector representations of various kinds of linguistic units in a document by(More)
Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of user generated sentiment data (e.g., reviews, blogs). Due to the mismatch among different domains, a sentiment classifier trained in one domain may not work well when directly applied to other domains. Thus, domain adaptation for sentiment(More)
Cross-lingual sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of data in a label-scarce target language by exploiting labeled data from a label-rich language. The fundamental challenge of cross-lingual learning stems from a lack of overlap between the feature spaces of the source language data and that(More)
Video popularity prediction plays a foundational role in many aspects of life, such as recommendation systems and investment consulting. Because of its technological and economic importance, this problem has been extensively studied for years. However, four constraints have limited most related works' usability. First, most feature oriented models are(More)
This paper proposes a novel topic model, Author-Conference Topic-Connection (ACTC) Model for academic network search. The ACTC Model extends the author-conference-topic (ACT) model by adding subject of the conference and the latent mapping information between subjects and topics. It simultaneously models topical aspects of papers, authors and conferences(More)