ویراساینس.
مقاله

EXTRACTION-BASED TEXT SUMMARIZATION USING FUZZY ANALYSIS

Farshad Kyoomarsi, Hamid Khosravi, Esfandiar Eslami, Mohsen Davoudi

چکیده

Due to the explosive growth of the world-wide web, automatictext summarization has become an essential tool for web users. In this paperwe present a novel approach for creating text summaries. Using fuzzy logicand word-net, our model extracts the most relevant sentences from an originaldocument. The approach utilizes fuzzy measures and inference on theextracted textual information from the document to find the most significantsentences. Experimental results reveal that the proposed approach extractsthe most relevant sentences when compared to other commercially availabletext summarizers. Text pre-processing based on word-net and fuzzy analysisis the main part of our work.

شکل‌ها (۵)

  • Figure 1. The Overall Structure of the Proposed Text Summarization System
    Figure 1. The Overall Structure of the Proposed Text Summarization Systemصفحه‌ی ۳
  • Figure 2. Left: The Fuzzy Sets of Keyword Fuzzy Analyzer for K1 and K2 and the Rule Matrix. Right: The Output Fuzzy Sets of Keyword Fuzzy Analyzer
    Figure 2. Left: The Fuzzy Sets of Keyword Fuzzy Analyzer for K1 and K2 and the Rule Matrix. Right: The Output Fuzzy Sets of Keyword Fuzzy Analyzerصفحه‌ی ۷
  • Figure 3. The 3-D Surfaces of Fuzzy Rules of Keyword and Summary-type Fuzzy Analyzers
    Figure 3. The 3-D Surfaces of Fuzzy Rules of Keyword and Summary-type Fuzzy Analyzersصفحه‌ی ۹
  • Figure 4. (Left) The Normalized Ranks of 12 Sentences, (Right) The Errors of Each Sentence between the Ranks of Fuzzy Logic Based Approach and Average of the Other Approaches
    Figure 4. (Left) The Normalized Ranks of 12 Sentences, (Right) The Errors of Each Sentence between the Ranks of Fuzzy Logic Based Approach and Average of the Other Approachesصفحه‌ی ۱۲
  • Figure 5. The Results Associated with All Models for Different Cr (English Case)
    Figure 5. The Results Associated with All Models for Different Cr (English Case)صفحه‌ی ۱۶

شکل‌ها از متن کامل مقاله برداشته شده‌اند و حقوقشان از آنِ نویسندگان و ناشر است. منبع: صفحه‌ی اصلی مقاله

اسناد مشابه

  • Biogeography-Based Optimization Algorithm for Automatic Extractive Text Summarization

    مقاله۲۰۱۷International Journal of Industrial Engineering and Productional Research-Hossein MirShojaee, Behrooz Masoumi, Esmaeel Zeinali

    Given the increasing number of documents, sites, online sources, and the users’ desire to quickly access information, automatic textual summarization has caught the attention of many researchers in this field. Researchers have presented different methods for text summarization as

  • Unsupervised Extraction of Diagnosis Codes from EMRs Using Knowledge-Based and Extractive Text Summarization Techniques

    سند علمی۲۰۱۳Advances in artificial intelligence : 26th Canadian Conference on Artificial Intelligence, Canadian AI 2013, Regina, SK, Canada, May 28-31, 2013, proceedings. Canadian Conference on Artificial IntelligenceRamakanth Kavuluru, Sifei Han, Daniel R. Harris

    Diagnosis codes are extracted from medical records for billing and reimbursement and for secondary uses such as quality control and cohort identification. In the US, these codes come from the standard terminology ICD-9-CM derived from the international classification of diseases

  • Survey on Extractive Text Summarization Approaches

    سند علمی۲۰۱۴M S Patil

    Due to increasing use of internet and online technologies or online data, there is vast increase in the electronic documents. When a data is being retrieved from such a huge collection of electronic documents, hundreds and thousands of documents are retrieved. Hence, for user, it

  • Evolutionary Algorithm for Extractive Text Summarization

    سند علمی۲۰۰۹Intelligent Information ManagementRasim M. Alguliyev, Ramiz M. Aliguliyev

    Text summarization is the process of automatically creating a compressed version of a given document preserving its information content. There are two types of summarization: extractive and abstractive. Extractive summarization methods simplify the problem of summarization into t

  • Terms Derived from Frequent Sequences for Extractive Text Summarization

    سند علمی۲۰۰۸CICLingYulia Ledeneva, Alexander F. Gelbukh, René Arnulfo García-Hernández

    Automatic text summarization helps the user to quickly understand large volumes of information. We present a languageand domain-independent statistical-based method for single-document extractive summarization, i.e., to produce a text summary by extracting some sentences from the

  • Toward a Gold Standard for Extractive Text Summarization

    سند علمی۲۰۱۰Canadian Conference on AIAlistair Kennedy, Stan Szpakowicz

    Extractive text summarization is the process of selecting relevant sentences from a collection of documents, perhaps only a single document, and arranging such sentences in a purposeful way to form a summary of this collection. The question arises just how good extractive summari