A trainable algorithm for summarizing news stories
نویسندگان
چکیده
This work proposes a trainable system for summarizing news and obtaining an approximate argumentative structure of the source text. To achieve these goals we use several techniques and heuristics, such as detecting the main concepts in the text, connectivity between sentences, occurrence of proper nouns, anaphors, discourse markers and a binary-tree representation (due to the use of an agglomerative clustering algorithm). The proposed system was evaluated on a set of 800 documents.
منابع مشابه
Genetic algorithm for summarizing news stories
This paper presents a new approach summarizing broadcast news using Genetic Algorithms. We propose to segment the news programs into stories, and then summarize stories by selecting from every one of them frames considered important to obtain an informative pictorial abstract. The summaries can help viewers to estimate the importance of the news video. Indeed, by consulting stories summaries we...
متن کاملNewsInEssence: A System For Domain-Independent, Real-Time News Clustering and Multi-Document Summarization
NEWSINESSENCE is a system for finding, visualizing and summarizing a topic-based cluster of news stories. In the generic scenario for NEWSINESSENCE, a user selects a single news story from a news Web site. Our system then searches other live sources of news for other stories related to the same event and produces summaries of a subset of the stories that it finds, according to parameters specif...
متن کاملAdaptive Representations for Tracking Breaking News on Twitter
Twitter is often the most up-to-date source for finding and tracking breaking news stories. Therefore, there is considerable interest in developing filters for tweet streams in order to track and summarize stories. This is a non-trivial text analytics task as tweets are short, and standard text similarity metrics often fail as stories evolve over time. In this paper we examine the effectiveness...
متن کاملFeature Selection for Trainable Multilingual Broadcast News Segmentation
Indexing and retrieving broadcast news stories within a large collection requires automatic detection of story boundaries. This video news story segmentation can use a wide range of audio, language, video, and image features. In this paper, we investigate the correlation between automatically-derived multimodal features and story boundaries in seven different broadcast news sources in three lan...
متن کاملTopic Models for Summarizing Novelty
We define temporal summaries of news stories as extracting as few sentences as possible from each event within a news topic, where the stories are presented one at a time and sentences from a story must be ranked before the next story can be considered. We outline an evaluation strategy that we have developed for this task and describe simple language models for capturing novelty and usefulness...
متن کاملذخیره 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 2000