Observa: Specialized Search
What is it?
OBSERVA is the intelligent search engine of OVTT. It is a meta search engine to access relevant information on technology transfer and innovation in Latin America.
Access to OBSERVA
For what?
You can find specialized and classified information related with Technology Transfer and Innovation, selected by criteria of interesting topics and industrial sectors and have access to specialized sources regarding R&D in Latin America.
OBSERVA also incorporates a Clustering system to suggest search results of interest. Using advanced algorithms, the system finds new hidden relevant categories in agreement with your desired search.
In addition, OBSERVA is a multilingual search engine. At the bottom of the search results page you can find options to search in different languages: Spanish, English and Portuguese.
What technology do we use?
OBSERVA is performed by the Group of Language Processing and Information Systems (GPLSI) at the University of Alicante (UA). The latest Semantic techniques of Human Language Technology (SLT) are used to provide solutions to business environment and to address the problem of collateral management and processing of large volumes of information and documentation from the web.
OBSERVA also incorporates automatic personalization and customization techniques, allowing the system to constantly learn and improve following the user needs. The applicability of this tool and its portability to other environments and needs is one of the scope of the system.
How it works?
Type the information you desire in the search field, press the search button and you will access to the OBSERVA results system.
Once in the search results panel you can work with the search results, filter the information by categories, industrial sectors and clustering according to your interests. In addition, if registered in the OVTT you can save your favourite searches and access to history. Join the OVTT.
OBSERVA is a search engine based on semantic techniques of the Human Language Technology (SLT). See more information in the Short Guide to the Semantic Web.
