Extracting Multilingual Natural-Language Patterns for RDF Predicates

Abstract. Most knowledge sources on the Data Web were extracted from structured or semi-structured data. Thus, they encompass solely a small fraction of the information available on the document-oriented Web. In this paper, we present BOA, a bootstrapping strategy for ex-tracting RDF from text. The idea behind BOA is to extract natural-language patterns that represent predicates found on the Data Web from unstructured data by using background knowledge from the Data Web. These patterns are used to extract instance knowledge from natural-language text. This knowledge is finally fed back into the Data Web, therewith closing the loop. The approach followed by BOA is quasi inde-pendent of the language in which the corpus is written. We demonstrate our approach by applying it to four different corpora and two different languages. We evaluate BOA on these data sets using DBpedia as back-ground knowledge. Our results show that we can extract several thousand new facts in one iteration with very high accuracy. Moreover, we provide the first multilingual repository of natural-language representations of predicates found on the Data Web.

DBpedia SPARQL Benchmark – Performance Assessment with Real Queries on Real Data

Abstract. Triple stores are the backbone of increasingly many Data Web appli-cations. It is thus evident that the performance of those stores is mission critical for individual projects as well as for data integration on the Data Web in gen-eral. Consequently, it is of central importance during the implementation of any of these applications to have a clear picture of the weaknesses and strengths of current triple store implementations. In this paper, we propose a generic SPARQL benchmark creation procedure, which we apply to the DBpedia knowledge base. Previous approaches often compared relational and triple stores and, thus, settled on measuring performance against a relational database which had been con-verted to RDF by using SQL-like queries. In contrast to those approaches, our benchmark is based on queries that were actually issued by humans and applica-tions against existing RDF data not resembling a relational schema. Our generic procedure for benchmark creation is based on query-log mining, clustering and SPARQL feature analysis. We argue that a pure SPARQL benchmark is more use-ful to compare existing triple stores and provide results for the popular triple store implementations Virtuoso, Sesame, Jena-TDB, and BigOWLIM. The subsequent comparison of our results with other benchmark results indicates that the per-formance of triple stores is by far less homogeneous than suggested by previous benchmarks. 1

Linking geographic vocabularies through WordNet

The linked open data (LOD) paradigm has emerged as a promising approach to structuring and sharing geospatial information. One of the major obstacles to this vision lies in the difficulties found in the automatic integration between heterogeneous vocabularies and ontologies that provides the semantic backbone of the growing constellation of open geo-knowledge bases. In this article, we show how to utilize WordNet as a semantic hub to increase the integration of LOD. With this purpose in mind, we devise Voc2WordNet, an unsupervised mapping technique between a given vocabulary and WordNet, combining intensional and extensional aspects of the geographic terms. Voc2WordNet is evaluated against a sample of human-generated alignments with the OpenStreetMap (OSM) Semantic Network, a crowdsourced geospatial resource, and the GeoNames ontology, the vocabulary of a large digital gazetteer. These empirical results indicate that the approach can obtain high precision and recall

Pregnant and non-pregnant women and low back pain-related differences on postural control measures during different balance tasks

Introduction: Low back pain (LBP) is the most common musculoskeletal complaint in pregnancy, being responsible for many negative impacts. Objective: To evaluate the effect of LBP on static and dynamic balance in pregnant women and whether pregnancy mediates the results compared to non-pregnant women. Methods: 44 women (mean age 30 yrs) participated voluntarily in this study: 16 pregnant women with LBP starting in pregnancy, 14 pregnant women without LBP and 14 non-pregnant women as a group control. Participants were assessed for static postural balance using a force platform and dynamic mobility balance using the Timed Up and Go (TUG) test. Results: The pregnant women with LBP showed significant (P < 0.04, for mean, d= 1,2) poor postural balance in static tests (force platform), in the area of COP eyes open. In dynamic balance (TUG test), statistical difference was found between the groups (P 0.038) and the effect size were moderate to strong in the comparison between the three groups. The most sensitive differences were reported mainly between pregnant women with LBP versus non-pregnant control group in balance measures from force platform. Conclusion: The findings indicate that LBP associated to pregnant clinical status can decrease the balance capacity in women. These results have implication for balance evaluation and retraining in pregnant women with and without LBP from rehabilitation or prevention programs

The TMS Map Scales with Increased Stimulation Intensity and Muscle Activation

One way to study cortical organisation, or its reorganisation, is to use transcranial magnetic stimulation (TMS) to construct a map of corticospinal excitability. TMS maps are reported to be acquired with a wide variety of stimulation intensities and levels of muscle activation. Whilst MEPs are known to increase both with stimulation intensity and muscle activation, it remains to be established what the effect of these factors is on the map's centre of gravity (COG), area, volume and shape. Therefore, the objective of this study was to systematically examine the effect of stimulation intensity and muscle activation on these four key map outcome measures. In a first experiment, maps were acquired with a stimulation intensity of 110, 120 and 130% of resting threshold. In a second experiment, maps were acquired at rest and at 5, 10, 20 and 40% of maximum voluntary contraction. Map area and map volume increased with both stimulation intensity (P 0.09 in all cases). This result indicates the map simply scales with stimulation intensity and muscle activation

Development of a national pain management competency profile to guide entry-level physiotherapy education in Canada

Background: National strategies from North America call for substantive improvements in entry-level pain management education to help reduce the burden of chronic pain. Past work has generated a valuable set of interprofessional pain management competencies to guide the education of future health professionals. However, there has been very limited work that has explored the development of such competencies for individual professions in different regions. Developing profession-specific competencies tailored to the local context is a necessary first step to integrate them within local regulatory systems. Our group is working toward this goal within the context of entry-level physiotherapy (PT) programs across Canada. Aims: This study aimed to create a consensus-based competency profile for pain management, specific to the Canadian PT contextMethods: A modified Delphi was used to achieve consensus across Canadian university-based and clinical pain educators. Results: Representatives from 14 entry-level PT programs (93% of Canadian programs) and six clinical educators were recruited. After two rounds, a total of 15 competencies reached the pre-determined endorsement threshold (75%). Most participants (85%) reported being "very satisfied" with the process. Conclusions: This process achieved consensus on a novel pain management competency profile specific to the Canadian PT context. The resulting profile delineates the necessary abilities required by physiotherapists to manage pain upon entry-to-practice. Participants were very satisfied with the process. This study also contributes to the emerging literature on integrated research in pain management by profiling research methodology that can be used to inform related work in other health professions and regions

Differences between Pygmy and Non-Pygmy hunting in Congo Basin forests

We use data on game harvest from 60 Pygmy and non-Pygmy settlements in the Congo Basin forests to examine whether hunting patterns and prey profiles differ between the two hunter groups. For each group, we calculate hunted animal numbers and biomass available per inhabitant, P, per year (harvest rates) and killed per hunter, H, per year (extraction rates). We assess the impact of hunting of both hunter groups from estimates of numbers and biomass of prey species killed per square kilometre, and by examining the proportion of hunted taxa of low, medium and high population growth rates as a measure of their vulnerability to overhunting. We then map harvested biomass (kg-1P-1Yr-1) of bushmeat by Pygmies and non-Pygmies throughout the Congo Basin. Hunting patterns differ between Pygmies and non-Pygmies; Pygmies take larger and different prey and non-Pygmies sell more for profit. We show that non-Pygmies have a potentially more severe impact on prey populations than Pygmies. This is because non-Pygmies hunt a wider range of species, and twice as many animals are taken per square kilometre. Moreover, in non-Pygmy settlements there was a larger proportion of game taken of low population growth rate. Our harvest map shows that the non-Pygmy population may be responsible for 27 times more animals harvested than the Pygmy population. Such differences indicate that the intense competition that may arise from the more widespread commercial hunting by non-Pygmies is a far more important constraint and source of conflict than are protected areas