EP 1974292 A1 20081001 - A KNOWLEDGE CORRELATION SEARCH ENGINE
Title (en)
A KNOWLEDGE CORRELATION SEARCH ENGINE
Title (de)
WISSENKORRELATIONS-SUCHMASCHINE
Title (fr)
MOTEUR DE RECHERCHE COMPRENANT UN MECANISME DE MISE EN CORRELATION DES INFORMATIONS
Publication
Application
Priority
- US 2006025101 W 20060628
- US 27356805 A 20051114
- US 31483505 A 20051221
Abstract (en)
[origin: WO2007061451A1] Clauses are important for a variety of NLP tasks such as predicting phrasing in text-to- speech synthesis and inferring text alignment for machine translation (Ejerhed 1988, Leffa 1998, Papageorgiou 1997). The Computational Natural Language Learning 2001 shared task (Sang & Déjean 2001) set the goal of identifying clause boundaries in text using machine learning methods. Systems created for the task predicted a label for each word specifying the number of clauses starting and ending at that position in the sentence without differentiating between clause types. This work extends that of the shared task in several ways: (1) performance bounds are explored, (2) an attempt is made to distinguish 'main' and 'subordinate' clauses, and (3) Winnow and maximum entropy, model classes proven effective in similar domains yet not previously employed for the task, are applied to the problem.
IPC 8 full level
G06F 17/30 (2006.01)
CPC (source: EP)
G06F 16/951 (2018.12)
Designated contracting state (EPC)
DE FR GB
DOCDB simple family (publication)
WO 2007061451 A1 20070531; CN 101310274 A 20081119; CN 101310274 B 20130417; EP 1974292 A1 20081001; EP 1974292 A4 20090401; JP 2009528581 A 20090806; JP 4864095 B2 20120125
DOCDB simple family (application)
US 2006025101 W 20060628; CN 200680042357 A 20060628; EP 06774152 A 20060628; JP 2008541146 A 20060628