Articles by Michal Laclavik

Michal joined Magnetic in February 2014 working as a Data Scientist, where he works on search query intent understanding. He has more than ten years R&D experience in the fields of Semantic Technologies, Information Retrieval, and Big Data technologies. Michal earned his PhD at the Slovak Academy of Sciences, where he worked as a researcher on several EU funded projects. He has also lectured on Information Retrieval at the Slovak University of Technology.

Michal can be found on the web at:


  1. Detecting Brands in User Search Queries

    Capturing user intent with brands can be valuable, especially in online advertising. In the online advertising domain, brand detection can help capture user interests and improve user modeling, which, in turn, can lead to an increase in precision of user targeting with ads relevant to their interests and needs.

  2. SKIP, The Search Keyword Intent Predictor

    Magnetic specializes in search retargeting, thus we really need to understand our users’ searches — it is our bread and butter. We need to recognize what a user’s search means in an understandable way for both humans and computers. This is why we map each search to a category (e.g. “Automotive”), brand (e.g. “BMW”), or other intent data. Our keyword categorization service and Search Keyword Intent Predictor (SKIP) is our core technology which addresses this need.