Incorporating Structured Commonsense Knowledge in Story Completion

The ability to select an appropriate story ending is the first step towards perfect narrative comprehension. Story ending prediction requires not only the explicit clues within the context, but also the implicit knowledge (such as commonsense) to construct a reasonable and consistent story. However, most previous approaches do not explicitly use background commonsense knowledge. We present a neural story ending selection model that integrates three types of information: narrative sequence, sentiment evolution and commonsense knowledge. Experiments show that our model outperforms state-of-the-art approaches on a public dataset, ROCStory Cloze Task , and the performance gain from adding the additional commonsense knowledge is significant

Mapping an ancient historian in a digital age: the Herodotus Encoded Space-Text-Image Archive (HESTIA)

HESTIA (the Herodotus Encoded Space-Text-Imaging Archive) employs the latest digital technology to develop an innovative methodology to the study of spatial data in Herodotus' Histories. Using a digital text of Herodotus, freely available from the Perseus on-line library, to capture all the place-names mentioned in the narrative, we construct a database to house that information and represent it in a series of mapping applications, such as GIS, GoogleEarth and GoogleMap Timeline. As a collaboration of academics from the disciplines of Classics, Geography, and Archaeological Computing, HESTIA has the twin aim of investigating the ways geography is represented in the Histories and of bringing Herodotus' world into people's homes

Finding Support Documents with a Logistic Regression Approach

Entity retrieval finds the relevant results for a user’s information needs at a finer unit called “entity”. To retrieve such entity, people usually first locate a small set of support documents which contain answer entities, and then further detect the answer entities in this set. In the literature, people view the support documents as relevant documents, and their findings as a conventional document retrieval problem. In this paper, we will state that finding support documents and that of relevant documents, although sounds similar, have important differences. Further, we propose a logistic regression approach to find support documents. Our experiment results show that the logistic regression method performs significantly better than a baseline system that treat the support document finding as a conventional document retrieval problem

Status and potential of bacterial genomics for public health practice : a scoping review

Background: Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist’s perspective. Methods: In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed. Results: Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data. Conclusions: For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist’s perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance

Information extraction

In this paper we present a new approach to extract relevant information by knowledge graphs from natural language text. We give a multiple level model based on knowledge graphs for describing template information, and investigate the concept of partial structural parsing. Moreover, we point out that expansion of concepts plays an important role in thinking, so we study the expansion of knowledge graphs to use context information for reasoning and merging of templates

Zinc intake, status and indices of cognitive function in adults and children: a systematic review and meta-analysis

In developing countries, deficiencies of micronutrients are thought to have a major impact on child development; however, a consensus on the specific relationship between dietary zinc intake and cognitive function remains elusive. The aim of this systematic review was to examine the relationship between zinc intake, status and indices of cognitive function in children and adults. A systematic literature search was conducted using EMBASE, MEDLINE and Cochrane Library databases from inception to March 2014. Included studies were those that supplied zinc as supplements or measured dietary zinc intake. A meta-analysis of the extracted data was performed where sufficient data were available. Of all of the potentially relevant papers, 18 studies met the inclusion criteria, 12 of which were randomised controlled trials (RCTs; 11 in children and 1 in adults) and 6 were observational studies (2 in children and 4 in adults). Nine of the 18 studies reported a positive association between zinc intake or status with one or more measure of cognitive function. Meta-analysis of data from the adult’s studies was not possible because of limited number of studies. A meta-analysis of data from the six RCTs conducted in children revealed that there was no significant overall effect of zinc intake on any indices of cognitive function: intelligence, standard mean difference of <0.001 (95% confidence interval (CI) –0.12, 0.13) P=0.95; executive function, standard mean difference of 0.08 (95% CI, –0.06, 022) P=0.26; and motor skills standard mean difference of 0.11 (95% CI –0.17, 0.39) P=0.43. Heterogeneity in the study designs was a major limitation, hence only a small number (n=6) of studies could be included in the meta-analyses. Meta-analysis failed to show a significant effect of zinc supplementation on cognitive functioning in children though, taken as a whole, there were some small indicators of improvement on aspects of executive function and motor development following supplementation but high-quality RCTs are necessary to investigate this further