Identifying Web Tables - Supporting a Neglected Type of Content on the Web

The abundance of the data in the Internet facilitates the improvement of extraction and processing tools. The trend in the open data publishing encourages the adoption of structured formats like CSV and RDF. However, there is still a plethora of unstructured data on the Web which we assume contain semantics. For this reason, we propose an approach to derive semantics from web tables which are still the most popular publishing tool on the Web. The paper also discusses methods and services of unstructured data extraction and processing as well as machine learning techniques to enhance such a workflow. The eventual result is a framework to process, publish and visualize linked open data. The software enables tables extraction from various open data sources in the HTML format and an automatic export to the RDF format making the data linked. The paper also gives the evaluation of machine learning techniques in conjunction with string similarity functions to be applied in a tables recognition task.Comment: 9 pages, 4 figure

Fungal volatile organic compounds: emphasis on their plant growth-promoting

Fungal volatile organic compounds (VOCs) commonly formed bioactive interface between plants and countless of microorganisms on the above- and below-ground plant-fungus interactions. Fungal-plant interactions symbolize intriguingly biochemical complex and challenging scenarios that are discovered by metabolomic approaches. Remarkably secondary metabolites (SMs) played a significant role in the virulence and existence with plant-fungal pathogen interaction; only 25% of the fungal gene clusters have been functionally identified, even though these numbers are too low as compared with plant secondary metabolites. The current insights on fungal VOCs are conducted under lab environments and to apply small numbers of microbes; its molecules have significant effects on growth, development, and defense system of plants. Many fungal VOCs supported dynamic processes, leading to countless interactions between plants, antagonists, and mutualistic symbionts. The fundamental role of fungal VOCs at field level is required for better understanding, so more studies will offer further constructive scientific evidences that can show the cost-effectiveness of ecofriendly and ecologically produced fungal VOCs for crop welfare

From Tables to Frames

Pivk A, Cimiano P, Sure Y. From Tables to Frames. Web Semantics: Science, Services and Agents on the World Wide Web. 2005;3(2-3):132-146

Automatic Extraction of Structurally Coherent Mini-Taxonomies

International audienceToday, ontologies are being used to model a domain of knowledge in semantic web. OWL is considered to be the main language for developing such ontologies. It is based on the XML model, which inherently follows the hierarchical structure. In this paper we demonstrate an automatic approach for emergent semantics modeling of ontologies. We follow the collaborative ontology construction method without the direct interaction of domain users, engineers or developers. A very important characteristic of an ontology is its hierarchical structure of concepts. We consider large sets of domain specific hierarchical structures as trees and apply frequent sub-tree mining for extracting common hierarchical patterns. Our experiments show that these hierarchical patterns are good enough to represent and describe the concepts for the domain ontology. The technique further demonstrates the construction of the taxonomy of domain ontology. In this regard we consider the largest frequent tree or a tree created by merging the set of largest frequent sub-trees as the taxonomy. We argue in favour of the trustabilty for such a taxonomy and related concepts, since these have been extracted from the structures being used with in the specified domain

Theoretical foundations for enabling a web of knowledge

Abstract. The current web is a web of linked pages. Frustrated user