Comparing and Benchmarking Semantic Measures Using SMComp

The goal of the semantic measures is to compare pairs of concepts, words, sentences or named entities. Their categorization depends on what they measure. If a measure only considers taxonomy relationships is a similarity measure; if it considers all type of relationships it is a relatedness measure. The evaluation process of these measures usually relies on semantic gold standards. These datasets, with several pairs of words with a rating assigned by persons, are used to assess how well a semantic measure performs. There are a few frameworks that provide tools to compute and analyze several well-known measures. This paper presents a novel tool - SMComp - a testbed designed for path-based semantic measures. At its current state, it is a domain-specific tool using three different versions of WordNet. SMComp has two views: one to compute semantic measures of a pair of words and another to assess a semantic measure using a dataset. On the first view, it offers several measures described in the literature as well as the possibility of creating a new measure, by introducing Java code snippets on the GUI. The other view offers a large set of semantic benchmarks to use in the assessment process. It also offers the possibility of uploading a custom dataset to be used in the assessment

Sampo-UI: A Full Stack JavaScript Framework for Developing Semantic Portal User Interfaces

This paper presents a new software framework, SAMPO-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the SAMPO-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. SAMPO-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.Peer reviewe

Multi-user investigation organizer

A system that allows a team of geographically dispersed users to collaboratively analyze a mishap event. The system includes a reconfigurable ontology, including instances that are related to and characterize the mishap, a semantic network that receives, indexes and stores, for retrieval, viewing and editing, the instances and links between the instances, a network browser interface for retrieving and viewing screens that present the instances and links to other instances and that allow editing thereof, and a rule-based inference engine, including a collection of rules associated with establishment of links between the instances. A possible conclusion arising from analysis of the mishap event may be characterized as one or more of: not a credible conclusion; an unlikely conclusion; a credible conclusion; conclusion needs analysis; conclusion needs supporting data; conclusion proposed to be closed; and an un-reviewed conclusion

The role of ontology in information management

The question posed in this thesis is how the use of ontologies by information systems affects their development and their performance. Several aspects about ontologies are presented, namely design and implementation issues, representational languages, and tools for ontology manipulation. The effects of the combination of ontologies and information systems are then investigated. An ontology-based tool to identify email message features is presented, and its implementation and execution details are discussed. The use of ontologies by information systems provides a better understanding about their requirements, reduces their development time, and supports knowledge management during execution time

HESML: A scalable ontology-based semantic similarity measures library with a set of reproducible experiments and a replication dataset

This work is a detailed companion reproducibility paper of the methods and experiments proposed by Lastra-Díaz and García-Serrano in (2015, 2016) [56–58], which introduces the following contributions: (1) a new and efficient representation model for taxonomies, called PosetHERep, which is an adaptation of the half-edge data structure commonly used to represent discrete manifolds and planar graphs; (2) a new Java software library called the Half-Edge Semantic Measures Library (HESML) based on PosetHERep, which implements most ontology-based semantic similarity measures and Information Content (IC) models reported in the literature; (3) a set of reproducible experiments on word similarity based on HESML and ReproZip with the aim of exactly reproducing the experimental surveys in the three aforementioned works; (4) a replication framework and dataset, called WNSimRep v1, whose aim is to assist the exact replication of most methods reported in the literature; and finally, (5) a set of scalability and performance benchmarks for semantic measures libraries. PosetHERep and HESML are motivated by several drawbacks in the current semantic measures libraries, especially the performance and scalability, as well as the evaluation of new methods and the replication of most previous methods. The reproducible experiments introduced herein are encouraged by the lack of a set of large, self-contained and easily reproducible experiments with the aim of replicating and confirming previously reported results. Likewise, the WNSimRep v1 dataset is motivated by the discovery of several contradictory results and difficulties in reproducing previously reported methods and experiments. PosetHERep proposes a memory-efficient representation for taxonomies which linearly scales with the size of the taxonomy and provides an efficient implementation of most taxonomy-based algorithms used by the semantic measures and IC models, whilst HESML provides an open framework to aid research into the area by providing a simpler and more efficient software architecture than the current software libraries. Finally, we prove the outperformance of HESML on the state-of-the-art libraries, as well as the possibility of significantly improving their performance and scalability without caching using PosetHERep