Text summarization with NLTK

The target of the automatic text summarization is to reduce a textual document to a summary that retains the pivotal points of the original document. The research about text summarization is very active and during the last years many summarization algorithms have been proposed.
In this post we will see how to implement a simple text summarizer using the NLTK library (which we also used in a previous post) and how to apply it to some articles extracted from the BBC news feed. The algorithm that we are going to see tries to extract one or more sentences that cover the main topics of the original document using the idea that, if a sentences contains the most recurrent words in the text, it probably covers most of the topics of the text. Here's the Python class that implements the algorithm:

from nltk.tokenize import sent_tokenize,word_tokenize
from nltk.corpus import stopwords
from collections import defaultdict
from string import punctuation
from heapq import nlargest

class FrequencySummarizer:
  def __init__(self, min_cut=0.1, max_cut=0.9):
    """
     Initilize the text summarizer.
     Words that have a frequency term lower than min_cut 
     or higer than max_cut will be ignored.
    """
    self._min_cut = min_cut
    self._max_cut = max_cut 
    self._stopwords = set(stopwords.words('english') + list(punctuation))

  def _compute_frequencies(self, word_sent):
    """ 
      Compute the frequency of each of word.
      Input: 
       word_sent, a list of sentences already tokenized.
      Output: 
       freq, a dictionary where freq[w] is the frequency of w.
    """
    freq = defaultdict(int)
    for s in word_sent:
      for word in s:
        if word not in self._stopwords:
          freq[word] += 1
    # frequencies normalization and fitering
    m = float(max(freq.values()))
    for w in freq.keys():
      freq[w] = freq[w]/m
      if freq[w] >= self._max_cut or freq[w] <= self._min_cut:
        del freq[w]
    return freq

  def summarize(self, text, n):
    """
      Return a list of n sentences 
      which represent the summary of text.
    """
    sents = sent_tokenize(text)
    assert n <= len(sents)
    word_sent = [word_tokenize(s.lower()) for s in sents]
    self._freq = self._compute_frequencies(word_sent)
    ranking = defaultdict(int)
    for i,sent in enumerate(word_sent):
      for w in sent:
        if w in self._freq:
          ranking[i] += self._freq[w]
    sents_idx = self._rank(ranking, n)    
    return [sents[j] for j in sents_idx]

  def _rank(self, ranking, n):
    """ return the first n sentences with highest ranking """
    return nlargest(n, ranking, key=ranking.get)

The FrequencySummarizer tokenizes the input into sentences then computes the term frequency map of the words. Then, the frequency map is filtered in order to ignore very low frequency and highly frequent words, this way it is able to discard the noisy words such as determiners, that are very frequent but don't contain much information, or words that occur only few times. And finally, the sentences are ranked according to the frequency of the words they contain and the top sentences are selected for the final summary.

To test the summarizer, let's create a function that extract the natural language from a html page using BeautifulSoup:

import urllib2
from bs4 import BeautifulSoup

def get_only_text(url):
 """ 
  return the title and the text of the article
  at the specified url
 """
 page = urllib2.urlopen(url).read().decode('utf8')
 soup = BeautifulSoup(page)
 text = ' '.join(map(lambda p: p.text, soup.find_all('p')))
 return soup.title.text, text

We can finally apply our summarizer on a set of articles extracted from the BBC news feed:

feed_xml = urllib2.urlopen('http://feeds.bbci.co.uk/news/rss.xml').read()
feed = BeautifulSoup(feed_xml.decode('utf8'))
to_summarize = map(lambda p: p.text, feed.find_all('guid'))

fs = FrequencySummarizer()
for article_url in to_summarize[:5]:
  title, text = get_only_text(article_url)
  print '----------------------------------'
  print title
  for s in fs.summarize(text, 2):
   print '*',s

And here are the results:

----------------------------------
BBC News - Scottish independence: Campaigns seize on Scotland powers pledge
* Speaking ahead of a visit to apprentices at an engineering firm in 
Renfrew, Deputy First Minister Nicola Sturgeon said: Only a 'Yes' vote will 
ensure we have full powers over job creation - enabling us to create more 
and better jobs across the country.
* Asked if the move smacks of panic, Mr Alexander told BBC Breakfast: 
I don't think there's any embarrassment about placing policies on the 
front page of papers with just days two go.
----------------------------------
BBC News - US air strike supports Iraqi troops under attack
* Gabriel Gatehouse reports from the front line of Peshmerga-held territory 
in northern Iraq The air strike south-west of Baghdad was the first taken as 
part of our expanded efforts beyond protecting our own people and humanitarian 
missions to hit Isil targets as Iraqi forces go on offence, as outlined in the 
president's speech last Wednesday, US Central Command said.
* But Iran's Supreme Leader Ayatollah Ali Khamenei said on Monday that the US 
had requested Iran's co-operation via the US ambassador to Iraq.
----------------------------------
BBC News - Passport delay victims deserve refund, say MPs
* British adult passport costs Normal service - £72.50 Check  Send - 
Post Office staff check application correct and it is sent by Special Delivery 
- £81.25 Fast-Track - Applicant attends Passport Office in person and passport 
delivered within one week - £103 Premium - Passport available for collection 
on same day applicant attends Passport Office - £128 In mid-June it announced 
that - for people who could prove they were booked to travel within seven days 
and had submitted passport applications more than three weeks earlier - there 
would be a free upgrade to its fast-track service.
* The Passport Office has since cut the number of outstanding applications to 
around 90,000, but the report said: A number of people have ended up 
out-of-pocket due to HMPO's inability to meet its service standard.
----------------------------------
BBC News - UK inflation rate falls to 1.5%
* Howard Archer, chief UK and European economist at IHS Global Insight, 
said: August's muted consumer price inflation is welcome news for consumers' 
purchasing power as they currently continue to be hampered by very 
low earnings growth.
* Consumer Price Index (CPI) inflation fell to 1.5% from 1.6% in August, 
the Office for National Statistics said.
----------------------------------
BBC News - Thailand deaths: Police have 'number of suspects'
* The BBC's Jonathan Head, on Koh Tao, says police are focussing on the 
island's Burmese community BBC south-east Asia correspondent Jonathan Head 
said the police's focus on Burmese migrants would be quite controversial as 
Burmese people were often scapegoated for crimes in Thailand.
* By Jonathan Head, BBC south-east Asia correspondent The shocking death of 
the two young tourists has cast a pall over this scenic island resort Locals 
say they can remember nothing like it happening before.

Of course, the evaluation a text summarizer is not an easy task. But, from the results above we note that the summarizer often picked quoted text reported in the original article and that the sentences picked by the summarizer often represent decent insights if we consider the title of the article.