With the increasing development and growth of Web services on the World Wide Web, the demand of appropriate Web service selection approaches are unprecedentedly strong, and Quality-of-Service (QoS) based service computing is becoming an important issue of service-oriented computing. In most of previous works, the QoS values of services to users are all conceived to be known, however, lots of th...

There are many ways to communicate with people, the most representative of which is a conversation. A smooth conversation should not only be written in grammatically appropriate manner, but also deal subject conversation; this known as language ability. In past, ability has been evaluated by analysis/therapy experts. However, process time-consuming and costly. study, researchers developed Hally...

We envisioned responsive generic hierarchical text summarization with summaries organized by topic and paragraph based on hierarchical structure topic models. But we had to be sure that topic models were stable for the sampled corpora. To that end we developed a methodology for aligning multiple hierarchical structure topic models run over the same corpus under similar conditions, calculating a...

In real world industrial applications of topic modeling, the ability to capture gigantic conceptual space by learning an ultra-high dimensional topical representation, i.e., the so-called “big model”, is becoming the next desideratum after enthusiasms on ”big data”, especially for fine-grained downstream tasks such as online advertising, where good performances are usually achieved by regressio...

In the text literature, many topic models were proposed to represent documents and words as topics or latent topics in order to process text effectively and accurately. In this paper, we propose LDACLM or Latent Dirichlet Allocation Category Language Model for text categorization and estimate parameters of models by variational inference. As a variant of Latent Dirichlet Allocation Model, LDACL...

Twitter is a crucial platform to get access to breaking news and timely information. However, due to questionable provenance, uncontrollable broadcasting, and unstructured languages in tweets, Twitter is hardly a trustworthy source of breaking news. In this paper, we propose a novel topic-focused trust model to assess trustworthiness of users and tweets in Twitter. Unlike traditional graph-base...

Many streams of real-world data, such as conversations or body movements, consist of relatively coherent segments, each characterized by particular topics or controllers. Making sense of these data requires simultaneously segmenting the sequences and inferring the structure of the segments. We present a hierarchical Bayesian model that can be used to break a sequence of utterances or movements ...

Previously topic models such as PLSI (Probabilistic Latent Semantic Indexing) and LDA (Latent Dirichlet Allocation) were developed for modeling the contents of plain texts. Recently, topic models for processing hypertexts such as web pages were also proposed. The proposed hypertext models are generative models giving rise to both words and hyperlinks. This paper points out that to better repres...

In the probabilistic topic models, the quantity of interest—a lowrank matrix consisting of topic vectors—is hidden in the text corpus matrix, masked by noise, and the Singular Value Decomposition (SVD) is a potentially useful tool for learning such a low-rank matrix. However, the connection between this low-rank matrix and the singular vectors of the text corpus matrix are usually complicated a...

In Automatic Text Processing tasks, documents are usually represented in the bag-ofwords space. However, this representation does not take into account the possible relations between words. We propose here a review of a family of document density estimation models for representing documents. Inside this family we derive another possible model: the Theme Topic Mixture Model (TTMM). This model as...