SENTENCE ORDERING USING CLUSTER CORRELATION AND PROBABILITY IN MULTI-DOCUMENTS SUMMARIZATION
Abstract: Most of the document
summary are arranged extractive by taking important sentences from the
document. Extractive based summarization often not consider the connection
sentence. A good sentence ordering
should aware about rhetorical relations such as cause-effect relation, topical
relevancy and chronological sequence which exist between the sentences. Based on this problem, we propose a new
method for sentence ordering in multi document summarization using cluster correlation
and probability for English documents. Sentences of multi-documents are grouped
based on similarity into clusters. Sentence extracted from each cluster to be a
summary that will be listed based on cluster correlation and probability. User
evaluation showed that the summary result of proposed method easier to
understanding than the previous method. The result of ROUGE method also shows
increase on sentence arrangement compared to previous method.
Author: I Gusti Agung Socrates
Adi Guna, Suci Nur Fauziah, Wanvy Arifha Saputra
Journal Code: jptkomputergg170007
Artikel Terkait :
Jp Teknik Komputer gg 2017
- Social Media Success Model for Knowledge Sharing (Scale Development and Validation)
- Histogram Equalization for Improving Quality of Low-Resolution Ultrasonography Images
- Research and Application of Development Model of Information Service for IOT of Oil and Gas Production Based on Cloud Architecture
- A Customized Reconfiguration Controller with Remote Direct ICAP Access for Dynamically Reconfigurable Platform
- Design LTE Microstrip Antenna Rectangular Patch with Beetle-Shaped Slot
- Design of Circular Patch with Double C-Shaped Slot Microstrip Antenna for LTE 1800 MHz
- A Three-Phase Grid-Connected PV System Based on SAPF for Power Quality Improvement
- Direct Torque Control: Stator Flux Regulation Improvement at Low Speed
- Brown’s Weighted Exponential Moving Average Implementation in Forex Forecasting
- A Crop Pests Image Classification Algorithm Based on Deep Convolutional Neural Network
- Hierarchical Gaussian Scale-Space on Androgenic Hair Pattern Recognition
- The Pessimistic Investor Sentiments Indicator in Social Networks
- 94 GHz Millimeter Wave Conducted Speech Enhancement
- Automatic Image Annotation Using CMRM with Scene Information
- Managers Perceptions towards the Success of E-performance Reporting System
- Binarization of Ancient Document Images based on Multipeak Histogram Assumption
- Automatic Summarization in Chinese Product Reviews
- Progressive Mining of Sequential Patterns Based on Single Constraint
- A Novel Space-time Discontinuous Galerkin Method for Solving of One-dimensional Electromagnetic Wave Propagations
- Development of Ammonia Gas Leak Detection and Location Method
- Compact Power Divider Integrated with Coupler and Microstrip Cavity Filter for X-band Surveillance Radar System
- Performance of Groundplane Shaping in Four-Element Dualband MIMO Antenna
- A Mamdani Fuzzy Model to Choose Eligible Student Entry
- Potential Usage Estimation of Ground Water using Spatial Association Rule Mining
- Investigation Study of Three-Level Cascaded H-bridge Multilevel Inverter