Text Summarization Model based on Redundancy-Constrained Knapsack Problem

نویسندگان

  • Hitoshi Nishikawa
  • Tsutomu Hirao
  • Toshiro Makino
  • Yoshihiro Matsuo
چکیده

In this paper we propose a novel text summarization model, the redundancy-constrained knapsack model. We add to the Knapsack problem a constraint to curb redundancy in the summary. We also propose a fast decoding method based on the Lagrange heuristic. Experiments based on ROUGE evaluations show that our proposals outperform a state-of-the-art text summarization model, the maximum coverage model, in finding the optimal solution. We also show that our decoding method quickly finds a good approximate solution comparable to the optimal solution of the maximum coverage model.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Robust Knapsack Based Constrained Portfolio Optimization

Many portfolio optimization problems deal with allocation of assets which carry a relatively high market price. Therefore, it is necessary to determine the integer value of assets when we deal with portfolio optimization. In addition, one of the main concerns with most portfolio optimization is associated with the type of constraints considered in different models. In many cases, the resulted p...

متن کامل

Text Summarization Using Cuckoo Search Optimization Algorithm

Today, with rapid growth of the World Wide Web and creation of Internet sites and online text resources, text summarization issue is highly attended by various researchers. Extractive-based text summarization is an important summarization method which is included of selecting the top representative sentences from the input document. When, we are facing into large data volume documents, the extr...

متن کامل

Single-Document Summarization as a Tree Knapsack Problem

Recent studies on extractive text summarization formulate it as a combinatorial optimization problem such as a Knapsack Problem, a Maximum Coverage Problem or a Budgeted Median Problem. These methods successfully improved summarization quality, but they did not consider the rhetorical relations between the textual units of a source document. Thus, summaries generated by these methods may lack l...

متن کامل

EXTRACTION-BASED TEXT SUMMARIZATION USING FUZZY ANALYSIS

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 docu...

متن کامل

Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization

We study the problem of predicting a set or list of options under knapsack constraint. The quality of such lists are evaluated by a submodular reward function that measures both quality and diversity. Similar to DAgger (Ross et al., 2010), by a reduction to online learning, we show how to adapt two sequence prediction models to imitate greedy maximization under knapsack constraint problems: CON...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012