C04-1136 empirical validation of the model on a collocation extraction task . 1 Introduction Many tools
C04-1141 , the linguistically motivated collocation extraction algorithm outscores all others
C04-1141 is standard nowadays ) allows collocation extraction algorithms to better control
D09-1051 as described in Section 2 for collocation extraction . baseline methods without using
A92-1025 pre-processing of relevant text , name and collocation extraction . In fact , the performance of
D09-1051 collocations . Both Chinese and English collocation extraction experiments indicate that our
D09-1051 general MWE research . <title> Collocation Extraction Using Monolingual Word Alignment
C04-1136 discussion . Empirical validation on a collocation extraction task has confirmed the usefulness
D09-1051 examine the effect of 0max on collocation extraction , we used several different 0max
C04-1136 alone . In the example of the collocation extraction task , randomness is mainly introduced
D09-1051 , we implement a MWA tool for collocation extraction , which uses similar training
C04-1141 particular the linguistically grounded collocation extraction algorithm , and the experimental
C96-1097 the procedure of uninterrupted collocation extraction . This can be easily performed
C04-1136 her comparative evaluation of collocation extraction methods . She is aware , though
D09-1051 &gt; 6 ) Chinese collocations . 2 Collocation Extraction With Mono - lingual Word Alignment
D11-1073 frequently used for MWU detection and collocation extraction ( e.g. Schone and Jurafsky (
C04-1141 there have been many studies on collocation extraction and mining using only statistical
D12-1123 widely used in many tasks , such as collocation extraction ( Liu et al. , 2009 ) , question
D11-1073 non-compositionality . These studies MWUs and collocation extraction , the general prob - compute
C04-1141 association measures typically used for collocation extraction , but also yields a valuable
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