Automatic extraction of semantic relationships between entity instances in an ontology is useful for attaching richer semantic metadata to documents. In this paper we propose an SVM based approach to hierarchical relation extraction, using features derived automatically from a number of GATE-based open-source language processing tools. In comparison to the previous works, we use several new fea...

Semantic relations among objects are primary semantic factors, which play the most important role for human and smart systems /machines to understand and control the situation in the context of connected systems. However, few existing works focus on the study of semantic relations from the mathematical view, though it would be the basis for further research on semantics. Existing research works...

We explore and evaluate the usefulness of semantic annotation, particularly semantic relations, in cross-language information retrieval in the medical domain. As the baseline for automatic semantic annotation we use UMLS, which specifies semantic relations between medical concepts. We developed two methods to improve the accuracy and yield of relations in CLIR: a method for relation filtering a...

We present a submission to the CogALex 2016 shared task on the corpus-based identification of semantic relations, using LexNET (Shwartz and Dagan, 2016), an integrated path-based and distributional method for semantic relation classification. The reported results in the shared task bring this submission to the third place on subtask 1 (word relatedness), and the first place on subtask 2 (semant...

This paper presents a model to compose semantic relations. The model is independent of any particular set of relations and uses an extended definition for semantic relations. This extended definition includes restrictions on the domain and range of relations and utilizes semantic primitives to characterize them. Primitives capture elementary properties between the arguments of a relation. An al...

The main obstacle to realize real semantic-based image retrieval is that semantic description of versatile images is difficult. The basic ideas of this paper are that the semantics of an object can be refined through top–down orthogonal semantic classification and that the semantics of an object can be reflected by the semantics of relevant objects and the semantic relationships between them. T...

The Linked Clinical Trials (LinkedCT) project aims at publishing the first open semantic web data source for clinical trials data. The database exposed by LinkedCT is generated by (1) transforming existing data sources of clinical trials into RDF, and (2) discovering semantic links between the records in the trials data and several other data sources. In this paper, we discuss several challenge...

This paper describes NTT DATA’s recognizing textual entailment(RTE) systems for NTCIR10 RITE2. We participate in four Japanese tasks, BC Subtask, Unit Test, Exam BC and Exam Search[5]. Our approach uses a ratio with the same semantic relations between words. It is necessary to recognize two semantic viewpoints, which are the semantic relation and the meaning between words in a sentence, in orde...

We present a graph-matching algorithm for semantic relation assignment. The algorithm is part of an interactive text analysis system. The system automatically extracts pairs of syntactic units from a text and assigns a semantic relation to each pair. This is an incremental learning algorithm, in which previously processed pairs and user feedback guide the process. After each assignment, the sys...

This paper reports on a study to explore how semantic relations can be used to expand a query for objects in an image. The study is part of a project ith the overall objective to provide semantic annotation and search facilities for a virtual collection of art resources. In this study we used semantic elations from WordNet for 15 image content queries. The results show that, next to the hyponym...