Wuhan University

About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Computer science & Population. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.

Topic Modeling for Short Texts with Auxiliary Word Embeddings

Abstract: For many applications that require semantic understanding of short texts, inferring discriminative and coherent latent topics from short texts is a critical and fundamental task. Conventional topic models largely rely on word co-occurrences to derive topics from a collection of documents. However, due to the length of each document, short texts are much more sparse in terms of word co-occurrences. Data sparsity therefore becomes a bottleneck for conventional topic models to achieve good results on short texts. On the other hand, when a human being interprets a piece of short text, the understanding is not solely based on its content words, but also her background knowledge (e.g., semantically related words). The recent advances in word embedding offer effective learning of word semantic relations from a large corpus. Exploiting such auxiliary word embeddings to enrich topic modeling for short texts is the main focus of this paper. To this end, we propose a simple, fast, and effective topic model for short texts, named GPU-DMM. Based on the Dirichlet Multinomial Mixture (DMM) model, GPU-DMM promotes the semantically related words under the same topic during the sampling process by using the generalized Polya urn (GPU) model. In this sense, the background knowledge about word semantic relatedness learned from millions of external documents can be easily exploited to improve topic modeling for short texts. Through extensive experiments on two real-world short text collections in two languages, we show that GPU-DMM achieves comparable or better topic representations than state-of-the-art models, measured by topic coherence. The learned topic representation leads to the best accuracy in text classification task, which is used as an indirect evaluation.

Multication Side Chain Anion Exchange Membranes

Abstract: Anion exchange membrane fuel cells (AEMFCs) have been developed as promising energy conversion devices for stationary and mobile applications due to their potentially low cost. To realize high-performance AEMFCs, new polymeric membranes are needed that are highly conductive and chemically stable. Here we report a systematic study of anion exchange membranes (AEMs) with multiple cations per side chain site to demonstrate how this motif can boost both the conductivity and stability of poly(2,6-dimethyl-1,4-phenylene oxide)-based AEMs. The highest conductivity, up to 99 mS/cm at room temperature, was observed for a triple-cation side chain AEM with 5 or 6 methylene groups between cations. This conductivity was considerably higher than AEM samples based on benzyltrimethylammonium or benzyldimethylhexylammonium groups with only one cation per side chain site. In addition to high conductivity, the multication side chain AEMs showed good alkaline and dimensional stabilities. High retention of ion exchange capaci...

Perovskite Solar Cell with an Efficient TiO2 Compact Film

Abstract: A perovskite solar cell with a thin TiO2 compact film prepared by thermal oxidation of sputtered Ti film achieved a high efficiency of 15.07%. The thin TiO2 film prepared by thermal oxidation is very dense and inhibits the recombination process at the interface. The optimum thickness of the TiO2 compact film prepared by thermal oxidation is thinner than that prepared by spin-coating method. Also, the TiO2 compact film and the TiO2 porous film can be sintered at the same time. This one-step sintering process leads to a lower dark current density, a lower series resistance, and a higher recombination resistance than those of two-step sintering. Therefore, the perovskite solar cell with the TiO2 compact film prepared by thermal oxidation has a higher short-circuit current density and a higher fill factor.