WHAT WE DO

Intelligenza artificiale

QBT develops algorithms and software in the fintech area, backed by a proof experience in the direct provision of services.
The mentioned experience has increased our know-how, consolidating our ability to develop tailored and customized management softwares in order to provide the best technological solution according to the specific customers’ needs.
Moreover, through a deep research and development activity we explored new areas of business turning into a point of reference in the field of Artificial Intelligence, and, in particular, in the Natural Language Processing and machine learning.
We develop all of our research activities thanks to a close cooperation with universities and research institutes, which represent the natural competence network at QBT.

Artificial Intelligence:
Natural Language Processing e Machine Learning

«The Artificial Intelligence (known with the English acronym AI) is a discipline belonging to the computer science which studies theories, methodologies and techniques allowing the design of hardware systems and software programs to supply the electronic computer with services that, to an ordinary observer, would seem to be exclusively human».

(Marco Somalvico)

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Specific definitions can be given by focusing on internal reasoning processes or on the external behavior of the intelligent system and using the similarity with human behavior or with an ideal behavior, called rational, as a measure of effectiveness.

The AI can simulate human intelligence in different ways, according to the processes activated:

  • acting humanly – the result of the operation performed by the intelligent system cannot be distinguished by the one belonging to the humankind;
  • thinking humanly – the process leading the intelligent system to solve a problem is very similar to the human one. This approach is linked to cognitive science;
  • thinking rationally – the process leading the intelligent system to solve a problem is a formal procedure referring to logic;
  • acting rationally - the process leading the intelligent system to solve a problem is the one that allows getting the best-expected result given the information available.

(source: Wikipedia)


Agent MOrSe 

Semantic research or Natural Language Processing:

  • does not rely on the simple search of Keywords;
  • solves the problems linked to morphology (singular/plural, infinitive verbs, etc.);
  • understands the meaning of the “context” thought, through the disambiguation of texts;
  • provides results that refer to the context even if the Keywords are not specifically present in the content.

An example is shown below:

The search “Penguins” will provide all the information sources reporting contents related to the funny “grey animals of the Southern Pole”, without such contents having to include strictly the word “Penguins”.


MOrSe 
(Semantic Search Engine) is a QBT platform, based on proprietary semantic technology, which supports customers in managing the information available in the most effective way, to get fundamental and strategic notions.
The platform can manage large data flows (text documents, multimedia, audio streams, web pages and social network) in 27 different languages.
The strength of the MOrSe platform are the specific thesauri defined for each specific application sector to conceptualize, classify and search for topics in the best way. This allows going beyond the limits of traditional technologies, which are based on keyword.
Designed and realized by experts of the sector together with CNR in Rome, MOrSe is adopted by qualified customers in Italy and Switzerland and it is used in different and multiple environments.

NewsMarket

NewsMarket

NewsMarket is a news analysis tool, appropriately trainable, developed to generate alarms and automated forecast, to propose to the investors.
The main idea is to create an automaton, which constantly analyzes news searching for correlations and trends, which says to the human being at the right time: “Given the current political and war situation in Lybia, ETF on oil and all the stocks related to the oil sector should be monitored. It is strongly recommended to pay attention to the ENI title, BP”.
The scientific basis of the NewsMarket system was presented during the Congress on Artificial Economics held on 29-30 August 2013 in Klagenfurt (Austria) and then published in the volume Springer: Artificial Economics and Self Organization, Lecture Notes in Economics and Mathematical Systems Volume 669, 2014, pp 133-145.

The second prototype, NewsMarket 2.0, was presented at the conference Carving Society: New frontiers in the study of social phenomena, held in Rome at LABSS-ISTC-CNR on 1st December 2014. Following the conference the paper NewsMarket 2.0: some empirical evidence was drafted. Its publication is now pending.