=Paper=
{{Paper
|id=Vol-2342/keynote2
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-2342/keynote2.pdf
|volume=Vol-2342
|dblpUrl=https://dblp.org/rec/conf/ecir/Martinez-Alvarez19
}}
==None==
<pdf width="1500px">https://ceur-ws.org/Vol-2342/keynote2.pdf</pdf>
<pre>
 Automatic Media analysis: From monitoring to Insights

                                             Miguel Martinez
                                                 Signal
                                      miguel.martinez@signal-ai.com




Abstract
One of the aspects of media analysis is brand monitoring which has traditionally focused on detecting and
distributing every mention of a given brand in the media as quickly as possible. This monitoring aspect, which
some companies such as Signal have automated using different IR and ML techniques, is critical for finding
relevant information. However, retrieving these documents is not enough. Leaders in diverse organisations will
use the knowledge derived from these relevant documents to change their decision making by understanding
their risks, opportunities (e.g. Acquiring companies in distress or expanding to new territories), but this is not
possible manually. Techniques to understand, organise and uncover the underlying insights that are hidden in
the thousands of documents are needed.
   This talk will focus on the media analysis space, the current monitoring approach (using Signal as an example)
and the future challenges and opportunities in the insights space, showcasing different challenges in the space
and that the IR community could support with.




Short Bio
Miguel Martinez is the co-founder and Chief Data Scientist of Signal, a growing UK company that analyses
millions of news articles every day in real-time in order to improve business intelligence and decision making.
During the last 6 years, Miguel has led the efforts to create and maintain the Signal Research team with strong
university collaborations, with the main goal of transforming the best research principles, models and algorithms
from academia into real, scalable products. Research interests include news processing, information retrieval,
text analysis, natural language processing and evaluation, among others. He completed his PhD from Queen
Mary University in 2014. During his time at Signal, the company has grown from 3 to more than 100 people in
3 continents and raised more than $30M. He has been awarded the Business Leader of Tomorrow award 2014
by Innovate UK and was included in the list of UK Business Innovators in 2016 by Bloomberg. Signal has
won numerous awards, including the Fujitsu AI Innovator in the Lloyds National Business awards 2018 and the
Hottest Enterprise SaaS or B2B in the Europas 2018. The team has also won the Best Demonstration award in
ECIR’15 and they are the main organisers of the NewsIR workshop.

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