Search Results for author:
Found 27 papers, 2 papers with code
Clustering-Based Article Identification in Historical Newspapers
This article focuses on the problem of identifying articles and recovering their text from within and across newspaper pages when OCR just delivers one text file per page.
Using Semantics for Granularities of Tokenization
First, we introduce DRUID, which is a method for detecting MWEs.
A Named Entity Recognition Shootout for German
We ask how to practically build a model for German named entity recognition (NER) that performs at the state of the art for both contemporary and historical texts, i. e., a big-data and a small-data scenario.
Document-based Recommender System for Job Postings using Dense Representations
Detecting the similarity between job advertisements is important for job recommendation systems as it allows, for example, the application of item-to-item based recommendations.
CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups
Complex word identification (CWI) is an important task in text accessibility.
Multilingual and Cross-Lingual Complex Word Identification
Complex Word Identification (CWI) is an important task in lexical simplification and text accessibility.
That's sick dude!: Automatic identification of word sense change across different timescales
In this paper, we propose an unsupervised method to identify noun sense changes based on rigorous analysis of time-varying text data available in the form of millions of digitized books.
Distributed Distributional Similarities of Google Books Over the Centuries
This paper introduces a distributional thesaurus and sense clusters computed on the complete Google Syntactic N-grams, which is extracted from Google Books, a very large corpus of digitized books published between 1520 and 2008.
