Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

First combined studies on Lorentz Invariance Violation from observations of astrophysical sources

International audienceImaging Atmospheric Cherenkov Telescopes study the highest energy (up to tens of TeV) photon emission coming from nearby and distant astrophysical sources, thus providing valuable results from searches for Lorentz Invariance Violation (LIV) effects. Highly variable, energetic and distant sources such as Pulsars and AGNs are the best targets for the Time-of-Flight LIV studies. However, the limited number of observations of AGN flares or of high-energy pulsed emission greatly restricts the potential of such studies, especially any potential LIV effects as a function of redshift. To address these issues, an inter-experiment working group has been established by the three major collaborations taking data with Imaging Atmospheric Cherenkov Telescopes (H.E.S.S., MAGIC and VERITAS) with the aim to increase sensitivity to any effects of LIV, together with an improved control of systematic uncertainties, by sharing data samples and developing joint analysis methods. This will allow an increase in the number of available sources and to perform a sensitive search for redshift dependencies. This presentation reviews the first combined maximum likelihood method analyses using simulations of published source observations done in the past with H.E.S.S., MAGIC and VERITAS. The results from analyses based on combined maximum likelihood methods, the strategies to deal with data from different types of sources and instruments, as well as future plans will be presented

Robust constraints on Lorentz Invariance Violation from H.E.S.S., MAGIC and VERITAS data combination

International audienceGamma-Ray bursts, flaring active galactic nuclei and pulsars are distant and energetic astrophysical sources, detected up to tens of TeV with Imaging Atmospheric Cherenkov Telescopes (IACTs). Due to their high variability, they are the most suitable sources for energy-dependent time-delay searches related to Lorentz Invariance Violation (LIV) predicted by some Quantum Gravity (QG) models. However, these studies require large datasets. A working group between the three major IACTs ground experiments - H.E.S.S., MAGIC and VERITAS - has been formed to address this issue and combine for the first time all the relevant data collected by the three experiments in a joint analysis.This proceeding will review the new standard combination method. The likelihood technique used to deal with data from different source types and instruments will be presented, as well as the way systematic uncertainties are taken into account. The method has been developed and tested using simulations based on published source observations from the three experiments. From these simulations, the performance of the method will be assessed and new light will be shed on time delays dependencies with redshift