Robust Algorithms for Combining Multiple Term Weighting Vectors for Document Classification

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Supervised Term Weighting Methods for URL Classification

Many term weighting methods are suggested in the literature for Information Retrieval and Text Categorization. Term weighting method, a part of feature selection process is not yet explored for URL classification problem. We classify a web page using its URL alone without fetching its content and hence URL based classification is faster than other methods. In this study, we investigate the use ...

متن کامل

Weighting observation vectors for robust speech recognition in noisy environments

In this paper, we propose a novel approach to robust speech recognition in noisy environments by discriminating the observation vectors. In conventional HMM-based speech recognition, all the observation vectors are treated with equal importance no matter how the corresponding speech segment is corrupted with noise. Our approach proposed here modifies the conventional decoder by weighting the li...

متن کامل

A New Document Embedding Method for News Classification

Abstract- Text classification is one of the main tasks of natural language processing (NLP). In this task, documents are classified into pre-defined categories. There is lots of news spreading on the web. A text classifier can categorize news automatically and this facilitates and accelerates access to the news. The first step in text classification is to represent documents in a suitable way t...

متن کامل

ADABOOST ENSEMBLE ALGORITHMS FOR BREAST CANCER CLASSIFICATION

With an advance in technologies, different tumor features have been collected for Breast Cancer (BC) diagnosis, processing of dealing with large data set suffers some challenges which include high storage capacity and time require for accessing and processing. The objective of this paper is to classify BC based on the extracted tumor features. To extract useful information and diagnose the tumo...

متن کامل

Information-theoretic Term Weighting Schemes for Document Clustering

We propose a new theory that quantifies information in probability distributions and derive a new document representation model for text clustering. By extending Shannon entropy to accommodate a non-linear relation between information and uncertainty, the proposed Least Information theory (LIT) provides insight into how terms can be weighted based on their probability distributions in documents...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The International Journal of Fuzzy Logic and Intelligent Systems

سال: 2016

ISSN: 1598-2645,2093-744X

DOI: 10.5391/ijfis.2016.16.2.81