The Importance of Traditional NLP Use Cases: Document Categorization and Entity Extraction NLP is booming. The pace of progress is impressive, the recognition of the field and what it has to offer is solid throughout the industry. Significant progress on issues that a few years ago where notoriously difficult to tackle: Question answering, natural language … Continue reading Categorization and Entity Extraction: These NLP veterans are relevant as ever
Tag: NER
Introduction La « reconnaissance d’entités nommées » consiste en l'extraction de séquences de mots à l’intérieur d’un document. Elle concerne d’abord les noms de personnes, d’organisations et de lieux, qui sont donc les entités nommées les plus typiques. Cependant, l’expression « reconnaissance d’entités nommées » ne rend pas compte du fait que la technique concerne … Continue reading Extraction de données chiffrées à partir de texte
Introduction Named Entity Recognition relates to the extraction of sequences of words from within a document. The technique is mostly used to extract names of people, organisations or places, which are therefore the most typical named entities. However, the term named entity recognition does not capture very well the importance of a fragment of text, … Continue reading Extracting Numbers from Text
Direct customer feedback In a highly competitive environment, knowing customer complaints and expectations has become a major challenge for all companies. Direct customer feedback has become an increasingly important contributor since the emergence of the Internet. Whether it be results from a speech recording converted into text, a comment from a marketing survey, an incoming … Continue reading Make the Voice of the Customer a Top Priority!