Internship at Yahoo! Research Labs

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1. I am very happy that our paper Language Intent Models for Inferring User Browsing Behavior by Manos Tsagkias, and Roi Blanco [1] has been accepted at SIGIR 2013, which will be held in Portland, Oregon, 12–16 August 2012. The paper was realized during my three-month internship at Yahoo! Research Barcelona during September–December 2011.

   References

   [1] Manos Tsagkias and Roi Blanco. 2012. Language intent models for inferring user browsing behavior. In Proceedings of the 35^th international ACM SIGIR conference on research and development in information retrieval (SIGIR ‘12). Association for Computing Machinery, New York, NY, USA, 335–344. ACM Link. PDF

   64.82% similar — Paper at SIGIR 2012 — Language Intent Models for Inferring User Browsing Behavior

2. 

   This summer I was happy to be back at the Special Interest Group in Information Retrieval (SIGIR), this time, in Pisa, Italy. Last time I was at SIGIR was in Portland back in 2012, where I was presenting the work I did at Yahoo! Barcelona. SIGIR is the top international conference on search engines, and it’s always good fun to hear the latest developments and exchange new ideas.

   36.77% similar — Presenting at the Industry Day at SIGIR 2016

3. At 904Labs we’ve developed a Query Intent/Understanding engine that hooks up on an e-shop’s data, bootstraps a knowledge graph, and it learns the mapping to directives automatically, i.e.,  without supervision (read without human annotations). It doesn’t require retraining nor external dependencies, and you can use it straight away, today, on your own Apache Solr or Elasticsearch index (from which we only read and never write and we never lock you in). If that sounds appealing, get in touch for a one month free trial!

   30.52% similar — What is a Query Intent/Understanding engine?

4. Today at 904Labs Search we’ve been having fun with the next version of our Query Intent/Understanding engine.

   If you don’t know what a Query Intent/Understanding engine is, here’s some background; otherwise keep reading.

   Our Query Intent/Understanding engine is closing to one year old, and it’s pretty cool: it can quickly boostrap a knowledge graph and continuously update it straight from our customer’s data. Since its introduction in September 2017, it has been tested in many different domains and languages and has shown substantial revenue uplift across customers.

   29.24% similar — New Version for 904Labs Query Intent Engine

5. Abstract

   In this paper we describe how Twitter is used in various languages. We observe notable differences between languages regarding the use of hashtags, links, mentions, and conversations. We propose two dimensions that can be used to classify languages, each of which is likely to require different ways of analysis.

   References

   [1] Wouter Weerkamp, Simon Carter, and Manos Tsagkias. 2011. How People use Twitter in Different Languages. In Web Science 2011. UVA Link; PDF.

   28.36% similar — Paper at WebScience 2011 — How People use Twitter in Different Languages

6. As eCommerce is becoming increasingly important, we recruited a small team of researchers from major and not so major players in the field to share views and experiences on theoretical and practical challenges and future directions on eCommerce search and recommendations. The result of our effort, Challenges and Research Opportunities in eCommerce Search and Recommendations is published in June 2020 issue of SIGIR Forum.

   This work is related to thoughts that I shared earlier on product search, and to 904Labs’ Query Intent engine and its magnificent results (examples).

   26.53% similar — Paper at SIGIR Forum — Challenges and Research Opportunities in eCommerce Search and Recommendations