Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloudSubmitted by bahar on Thu, 2016-01-07 17:09
We present an automatic workflow that performs text segmentation and entity extraction from scientific literature to primarily address Task 2 of the Semantic Publishing Challenge 2015. The proposed solution is composed of two subsystems: (i) A text mining pipeline, developed based on the GATE framework, which extracts structural and semantic entities, such as, authors' information and citations, from text and produces semantic (typed) annotations; and (ii) a flexible exporting module that translates the document annotations into RDF triples according to a custom mapping file.
As a new extension to our Semantic Assistants framework, the integration of Semantic Assistants for Liferay allows portals to automatically process textual content using state-of-the-art techniques from the Natural Language Processing (NLP) domain. The SA-Liferay integration aims at bringing NLP power to this popular portal system and its users in a seamless, user-friendly manner, realized as a ready-to-deploy custom portlet. With this new integration, we envision a new generation of web portals that can provide context-sensitive support through semantic analysis services, in particular based on NLP, allowing AI "assistants" support portal users with their tasks at hand.
Natural Language Processing for Web Portals: First release of the Semantic Assistants-Liferay Integration
A data portal is a web-based software application, which provides a central entry point to an enormous amount of heterogeneous data sources. These mostly heterogeneous information are aggregated from various sources and presented to users based on their assigned roles. Ideally, an intelligent portal must be able to offer content to users, taking into account contextual information beyond their roles and permissions. Our integration of Semantic Assistants for Liferay allows portals to automatically process textual content using state-of-the-art techniques from the Natural Language Processing (NLP) domain. The SA-Liferay integration aims at bringing the NLP power to this popular portal system and its users in a seamless, user-friendly manner, realized as a ready-to-deploy custom portlet.
Semantic Assistants support users in content retrieval, analysis, and development, by offering context-sensitive NLP services directly integrated with common desktop applications (word processors, email clients, Web browsers, ...), web information systems (wikis, portals) and mobile applications (based on Android). They are implemented through an open service-oriented architecture, using Semantic Web ontologies and W3C Web Services.
1.1. Info Sheets
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The Semantic Computing course (SOEN 691B) is offered at Concordia University, providing graduate students with a unique opportunity to study research and development of novel semantic software systems. The course is taught by Prof. René Witte and supported by team members from the Semantic Software Lab. Students from other universities in Québec can register for this course through CREPUQ.
This course provide an introduction to selected topics from Semantic Computing, including text mining, tagging and tag analysis, recommender systems, RDF and linked data, semantic desktops and semantic wikis.
Within this project, we investigated semantic support, included ontologies, linked data, and text mining, for genozymes for bioproducts and bioprocesses development.
Through the selection of appropriate technologies and their combination in a coherent system that brings measurable improvements to the users, we develop a semantic infrastructure in support of genomics-based lignocellulose research.