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An Interview with Jean-Luc Marini

Jean-Luc Marini of Search'XPR

What's the history of your firm?

After having spent 6 years of research in the field of artificial intelligence and data search at the Lyon University - Magellan Research Center, I was able to show that the concept of serendipity - that is accidental discovery of something you were not looking for – is actually the result of a “psycho-cognitive” mechanism. I have also been able to model and experiment this mechanism within a context of a community-based Meta search engine.

The serendipity “psycho-cognitive” occurs in the form of an unexpected recommendation which follows a search for content(s), person(s) or organization(s) within a digital memory that has not been successful and drifted into an exploratory wander phase.

This recommendation, with no obvious connection with the initial search, is striking one of the user’s topics of interest he had no conscience about before it is becoming effective.

Consecutively to my research, Olivier Figon, associate professor at SARI and business owner, and I created the company Search'XPR™ as of July 2011 in order to design a line of APIs allowing a flexible and robust integration of the serendipity “psycho-cognitive” principle into Big Data Enterprise Search and E-commerce applications.

The implementation of this principle opens a way for a new generation of applications embedding the recommendation technology developed by Search'XPR: the Serendipity Apps ™.

The technology developed by Search'XPR to recommend content(s), person(s), or organization(s) is a disruptive technology since it provides additional functionality to existing recommendation technologies into existing and mature markets like Big Data Enterprise Search or E-commerce.

In E-Commerce applications market, it allows an increase of both the conversion rate of visits into orders and the average basket.

In Big Data Enterprise Search market, it improves the efficiency of the intelligent search tools.

When did you become interested in intelligent search tools?

I worked more than twenty years in Information & Communication technologies, both within government and private sector ventures. I helped start many companies focused on EDMS and IT infrastructure. This professional path combined with the fact that I did a PhD in Information and Communication Sciences, a Master in Computer Science and a Bachelor of Science in Applied Mathematics pulled me into this technical sector. This passion, I live it all year long. In addition of being Search’XPR President, CEO and acting Research Center Director, I am also an Adjunct Professor at The Lyon University and an active member of The Magellan Research Center managing programs to improve data search tools based upon Artificial Intelligence.

Your firm has been investing in search and recommendation for several years. What are the general areas of your research activities?

At Search'XPR, our researches are mainly focused on new modes of information display according to various systems of sensorial representation, identification of communities and structuring shapes of network using graphs spectral properties, and organization of a new model for dynamic data and graphs storage within a distributed environment.

Many vendors argue that mash ups are and data fusion are "the way information retrieval will work going forward. How does your firm perceive this blend of search and user-accessible outputs?

This is not an issue for Search'XPR since we come in addition to data search systems (Information Retrieval Systems) embedded in Big Data or E-Commerce solutions. For us, the value of a data comes from its diversity.

The Search'XPR’s recommendation technology plays an important role in the user satisfaction. It does not take into account whether there is a structure or lack of structure of data. Its goal is to suggest a data content only based on user’s subconscious topics of interests and his for data search strategies.

Without divulging your firm's methods or clients, will you characterize a typical use case for your firm's search and recommendation capabilities?

Oorace™ APIs are for example used to integrate the serendipity feature into TV listings and VOD (video on demand) search and recommendation systems connected to the Internet. The feature is gaining leverage from the user’s behavior and his subconscious topics of interest not only linked to his TV listings and VOD searches but also linked to his searches and navigation on other online services offered by the operator of the Internet set top box. Because of this, the operator is able to offer the customer, during his navigation, some totally unexpected listings or VOD compared to its search topics but totally linked to his subconscious topics of interest. In the future, the associated ads agency will also be able to use this feature to offer the same way unexpected and well-targeted ads to the subscriber.

How do you integrate Search'XPR technology into a commercial application or a government agency proprietary application?

Search'XPR offers access to its technology via Oorace, a line of APIs (Application Program Interface) thru a REST protocol in SaaS mode on a cloud platform for conventional applications or in embedded mode for mobile applications. Whether it is for an E-commerce website for example or for a government agency proprietary application, the integration of the serendipity feature with the client application is therefore eased by a simple and effective method of implementation compatible with most of information systems present on the web.

How does an information retrieval engagement with your firm move through its life cycle?

The implementation of the serendipity feature is generally subject to a life cycle split in three phases:

  • An integration phase which initially capitalizes user’s experiences, usually applied to a sample of users
  • A generalization phase to all the users or subscribers depending on the client case (E-commerce platforms, social networks, dating sites ...), which inserts an additional dimension to the previous phase based on architecture and network
  • An evolution phase where availabilities of API updates bring additional functions to the serendipity feature.

There has been a surge in interest in putting "everything" in a repository and then manipulating the indexes to the information in the repository. Is your technology part of this trend?

From our perspective, because we are coming as addition to the current data search systems, the data storage problem does not speak the same way.

Search'XPR’s technology requires managing different types of data.

Data we are managing within our recommendation technology are not only structured data but also graphs for which we manage evolution over time.

Therefore our current storage architecture relies not only on a distributed non-relational data management system with a structured storage for large tables, but also on an object-oriented database using graph theory adapted for the use of graph type data.

In addition, Search'XPR is currently considering organizing a new model of dynamic data and graphs storage in distributed environment.

Visualization has been a great addition to briefings. On the other hand, visualization and other graphic eye candy can be a problem to those in stressful operational situations. What's your firm's approach to presenting "outputs" for end user or for mobile access?

Although our technology is complementing data search systems and therefore Intelligent Search solutions, Search'XPR is currently working on the development of new ways to present results depending on different kind of sensorial representation systems.

There seems to be a popular perception that the world will be doing computing via iPad devices and mobile phones. My concern is that serious computing infrastructures are needed and that users are "cut off" from access to more robust systems? How does your firm see the computing world over the next 12 to 18 months?

The implementation of our technology into mobile applications is absolutely not an issue since we work with RESTful web APIs (also called Expired RESTful web services). As an example, we are currently working with a company specialized in Ingame Advertising in order to implement our technology into games available on tablets and smartphones.

By the way, at Search'XPR, we decided to strengthen our development skills in order to be able to implement new psychological profiling devices currently under R & D.

How does your technology take advantage of the behavior of the consumer on Internet?

Big Data gives a particular prominence to a class of data remained unnoticed until recently or considered useless data: low information density data. This approach does not take into account in any data search the overall complexity of the reasoning of an individual and is ignoring the existence of a subconscious goal behind the conscious expressed goal.

With the advent of Big Data, our technology allows you to use in a different way data often viewed as unnecessary, because carrying a low meaning and therefore unnoticed by traditional semantics based systems, to link them to a subconscious goal and allow the integration of an emotional dimension as parameter into a model of marketing approach.

By using our technology, it becomes possible to benefit from the catalyst aspect of Big Data in order to expand the opportunities of behavioral analysis for the development of new tools value-creating like for example in E-commerce.

Where does a reader get more information about your firm?

Your readers can visit for more information our website at and/or contact Emmanuel Danten, our Managing Director North America. Our subsidiary Search’XPR Inc. is located 140 Broadway, 46th Floor, New York, NY 10005. His phone number is 1 (212)858-7671 and his email is .

Stephen E. Arnold, June 18, 2013

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