An Automat for the Semantic Processing of Structured Information

Using the database of the PuertoTerm project, an indexing system based on the cognitive model of Brigitte Enders was built. By analyzing the cognitive strategies of three abstractors, we built an automat that serves to simulate human indexing processes. The automat allows the texts integrated in the system to be assessed, evaluated and grouped by means of the bipartite spectral graph partitioning algorithm, which also permits visualization of the terms and the documents. The system features an ontology and a database to enhance its operativity. As a result of the application, we achieved better rates of exhaustivity in the indexing of documents, as well as greater precision and retrieval of information, with high levels of efficiency.Comment: IEEE Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on Date of Conference: Nov. 30 2009-Dec. 2 2009, Page(s): 85 - 8

Natural language understanding: instructions for (Present and Future) use

In this paper I look at Natural Language Understanding, an area of Natural Language Processing aimed at making sense of text, through the lens of a visionary future: what do we expect a machine should be able to understand? and what are the key dimensions that require the attention of researchers to make this dream come true

Linked Data for the Natural Sciences. Two Use Cases in Chemistry and Biology

Wiljes C, Cimiano P. Linked Data for the Natural Sciences. Two Use Cases in Chemistry and Biology. In: Proceedings of the Workshop on the Semantic Publishing (SePublica 2012). 2012: 48-59.The Web was designed to improve the way people work together. The Semantic Web extends the Web with a layer of Linked Data that offers new paths for scientific publishing and co-operation. Experimental raw data, released as Linked Data, could be discovered automatically, fostering its reuse and validation by scientists in different contexts and across the boundaries of disciplines. However, the technological barrier for scientists who want to publish and share their research data as Linked Data remains rather high. We present two real-life use cases in the fields of chemistry and biology and outline a general methodology for transforming research data into Linked Data. A key element of our methodology is the role of a scientific data curator, who is proficient in Linked Data technologies and works in close co-operation with the scientist