Edgar Meij

Edgar MeijThis is the website of Edgar Meij. I lead several groups of researchers and engineers at Bloomberg and we are working on improving search and discovery for Bloomberg, including the Question Answering systems as well as the Bloomberg Knowledge Graph, together with its value-add machine learning-based Analytics. I am also a senior scientist working on knowledge graphs, information retrieval, natural language processing, and machine learning. I am interested in advancing the state of the art in information retrieval and natural language processing at Web scale. My recent research has mainly focused on semantic search, namely, designing entity-oriented search systems that employ advanced NLP and machine learning techniques to improve user models, search, recommender systems, and content matching.

Before this, I was a research scientist at Yahoo Labs, working on various semantic search, query understanding, and recommender systems projects, employing knowledge graphs, query log analysis, machine learning, and distributed computing. Before that I did a post-doc at the Information and Language Processing Systems (ILPS) group of the Intelligent Systems Lab (ISLA) of the Informatics Institute of the University of Amsterdam. Research projects I have been involved there with include VL-e, CCCT, and Daeso. Most recently, I was working on DutchSemCor and LiMoSINe, two EU projects that center around semantic search, semantic annotations, and semantic information access. For the latter I was a workpackage leader.

In 2010 I finished my PhD under supervision of Maarten de Rijke. The topic of my PhD was leveraging conceptual knowledge from ontologies, thesauri, tags, annotations, or any other (structured) knowledge source to enhance information access. Information access – in this sense – entails retrieval and navigation of both documents and knowledge. To this end I am using statistical language modeling techniques, which are naturally capable of capturing language use and which I employ to bridge the semantic gap between (a priori defined) knowledge and (observed) language.1 Using this framework I am able to compare queries, documents, concepts, and relations on a conceptual level using language observations. More information can be found at http://phdthes.is/. In 2008 I spent some time in Barcelona, where I worked with Hugo Zaragoza and Peter Mika at Yahoo Labs. My research interests include, but are not limited by: (Semantic) Information Retrieval, the Semantic Web, Language Modeling, Big data, and Data and Text Mining.

I’m passionate about semantic search, information retrieval, search engines, semantic web, machine learning, information visualization, and mathematics and this website is my digital business card as well as my personal blog. I write on information retrieval, semantic web technologies, research in general, and, on occasion, stuff that doesn’t fit neatly into one of these categories. I also occasionally write about resources I discover or find interesting.

  1. Or, as Ludwig Wittgenstein said: “Meaning is use”. http://en.wikipedia.org/wiki/Ludwig_Wittgenstein []