Topic Extraction from Text Documents Using Multiple-Cause Networks
نویسندگان
چکیده
This paper presents an approach to the topic extraction from text documents using probabilistic graphical models. Multiple-cause networks with latent variables are used and the Helmholtz machines are utilized to ease the learning and inference. The learning in this model is conducted in a purely data-driven way and does not require prespecified categories of the given documents. Topic words extraction experiments on the TDT-2 collection are presented. Especially, document clustering results on a subset of TREC-8 ad-hoc task data show the substantial reduction of the inference time without significant deterioration of performance.
منابع مشابه
Automatic keyword extraction using Latent Dirichlet Allocation topic modeling: Similarity with golden standard and users' evaluation
Purpose: This study investigates the automatic keyword extraction from the table of contents of Persian e-books in the field of science using LDA topic modeling, evaluating their similarity with golden standard, and users' viewpoints of the model keywords. Methodology: This is a mixed text-mining research in which LDA topic modeling is used to extract keywords from the table of contents of sci...
متن کاملA review of text mining approaches and their function in discovering and extracting a topic
Background and aim: Four text mining methods are examined and focused on understanding and identifying their properties and limitations in subject discovery. Methodology: The study is an analytical review of the literature of text mining and topic modeling. Findings: LSA could be used to classify specific and unique topics in documents that address only a single topic. The other three text min...
متن کاملروش جدید متن‌کاوی برای استخراج اطلاعات زمینه کاربر به‌منظور بهبود رتبه‌بندی نتایج موتور جستجو
Today, the importance of text processing and its usages is well known among researchers and students. The amount of textual, documental materials increase day by day. So we need useful ways to save them and retrieve information from these materials. For example, search engines such as Google, Yahoo, Bing and etc. need to read so many web documents and retrieve the most similar ones to the user ...
متن کاملارائه مدلی برای استخراج اطلاعات از مستندات متنی، مبتنی بر متن‌کاوی در حوزه یادگیری الکترونیکی
As computer networks become the backbones of science and economy, enormous quantities documents become available. So, for extracting useful information from textual data, text mining techniques have been used. Text Mining has become an important research area that discoveries unknown information, facts or new hypotheses by automatically extracting information from different written documents. T...
متن کاملAdaptive Information Extraction from Structured Text Documents
Effective analysis of structured documents may decide on management information systems performance. In the paper, an adaptive method of information extraction from structured text documents is considered. We assume that documents belong to thematic groups and that required set of information may be determined ”apriori”. The knowledge of document structure allows to indicate blocks, where certa...
متن کامل