Combining Text and Formula Queries in Math Information Retrieval: Evaluation of Query Results Merging Strategies

Specific to Math Information Retrieval is combining text with mathematical formulae both in documents and in queries. Rigorous evaluation of query expansion and merging strategies combining math and standard textual keyword terms in a query are given. It is shown that techniques similar to those known from textual query processing may be applied in math information retrieval as well, and lead to a cutting edge performance. Striping and merging partial results from subqueries is one technique that improves results measured by information retrieval evaluation metrics like Bpref

Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter

Global events such as terrorist attacks are commented upon in social media, such as Twitter, in different languages and from different parts of the world. Most prior studies have focused on monolingual sentiment analysis, and therefore excluded an extensive proportion of the Twitter userbase. In this paper, we perform a multilingual comparative sentiment analysis study on the terrorist attack in Paris, during November 2015. In particular, we look at targeted sentiment, investigating opinions on specific entities, not simply the general sentiment of each tweet. Given the potentially inflammatory and polarizing effect that these types of tweets may have on attitudes, we examine the sentiments expressed about different targets and explore whether disproportionate reaction was expressed about such targets across different languages. Specifically, we assess whether the sentiment for French speaking Twitter users during the Paris attack differs from English-speaking ones. We identify disproportionately negative attitudes in the English dataset over the French one towards some entities and, via a crowdsourcing experiment, illustrate that this also extends to forming an annotator bias

Quantitative Analysis of Bloggers Collective Behavior Powered by Emotions

Large-scale data resulting from users online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study emergence of the emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite network of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion-classifier developed for this type of texts. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore robustness of these critical states, we design a network automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states

Uso combinado del LIDAR y medidas hiperspectrales para la teledetección de la fluorescencia y el perfil vertical del dosel

Revista oficial de la Asociación Española de Teledetección[EN] We report the development of a new LIDAR system (LASVEG) for airborne remote sensing of chlorophyll fluorescence (ChlF) and vertical profile of canopies. By combining laser-induced fluorescence (LIF), sun-induced fluorescence (SIF) and canopy height distribution, the new instrument will allow the simultaneous assessment of gross primary production (GPP), photosynthesis efficiency and above ground carbon stocks. Technical issues of the fluorescence LIDAR development are discussed and expected performances are presented.[ES] Se presenta el desarrollo de un nuevo sistema LIDAR (LASVEG) para la teledetección aerotransportada de la fluorescencia de la clorofila (ChlF) y el perfil vertical del dosel. Mediante la combinación de la fluorescencia inducida por láser (LIF), la fluorescencia inducida por el sol (SIF) y la distribución de la altura del dosel, el nuevo instrumento permitirá la evaluación simultánea de la producción primaria bruta (GPP), la eficiencia de la fotosíntesis y las reservas de carbono por encima del nivel del suelo. Se discuten cuestiones técnicas del desarrollo del LIDAR fluorescencia y se presentan las prestaciones previstasThis instrument is developed in the framework of the CALSIF project with the support of the French national agency ANR and the French space agency CNES.Ounis, A.; Bach, J.; Mahjoub, A.; Daumard, F.; Moya, I.; Goulas, Y. (2016). Combined use of LIDAR and hyperspectral measurements for remote sensing of fluorescence and vertical profile of canopies. Revista de Teledetección. (Special Issue):87-94. doi:10.4995/raet.2015.3982.SWORD8794Special Issu

A new flat shell finite element for the linear analysis of thin shell structures

In this paper, a new rectangular flat shell element denoted ‘ACM_RSBE5’ is presented. The new element is obtained by superposition of the new strain-based membrane element ‘RSBE5’ and the well-known plate bending element ‘ACM’. The element can be used for the analysis of any type of thin shell structures, even if the geometry is irregular. Comparison with other types of shell elements is performed using a series of standard test problems. A correlation study with an experimentally tested aluminium shell is also conducted. The new shell element proved to have a fast rate of convergence and to provide accurate results

Studying the Effect and Treatment of Misspelled Queries in Cross-Language Information Retrieval

[Abstract] The performance of Information Retrieval systems is limited by the linguistic variation present in natural language texts. Word-level Natural Language Processing techniques have been shown to be useful in reducing this variation. In this article, we summarize our work on the extension of these techniques for dealing with phrase-level variation in European languages, taking Spanish as a case in point. We propose the use of syntactic dependencies as complex index terms in an attempt to solve the problems deriving from both syntactic and morpho-syntactic variation and, in this way, to obtain more precise index terms. Such dependencies are obtained through a shallow parser based on cascades of finite-state transducers in order to reduce as far as possible the overhead due to this parsing process. The use of different sources of syntactic information, queries or documents, has been also studied, as has the restriction of the dependencies applied to those obtained from noun phrases. Our approaches have been tested using the CLEF corpus, obtaining consistent improvements with regard to classical word-level non-linguistic techniques. Results show, on the one hand, that syntactic information extracted from documents is more useful than that from queries. On the other hand, it has been demonstrated that by restricting dependencies to those corresponding to noun phrases, important reductions of storage and management costs can be achieved, albeit at the expense of a slight reduction in performance.Ministerio de Economía y Competitividad; FFI2014-51978-C2-1-RRede Galega de Procesamento da Linguaxe e Recuperación de Información; CN2014/034Ministerio de Economía y Competitividad; BES-2015-073768Ministerio de Economía y Competitividad; FFI2014-51978-C2-2-

CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands

The CEFLES2 campaign during the Carbo Europe Regional Experiment Strategy was designed to provide simultaneous airborne measurements of solar induced fluorescence and CO2 fluxes. It was combined with extensive ground-based quantification of leaf- and canopy-level processes in support of ESA's Candidate Earth Explorer Mission of the "Fluorescence Explorer" (FLEX). The aim of this campaign was to test if fluorescence signal detected from an airborne platform can be used to improve estimates of plant mediated exchange on the mesoscale. Canopy fluorescence was quantified from four airborne platforms using a combination of novel sensors: (i) the prototype airborne sensor AirFLEX quantified fluorescence in the oxygen A and B bands, (ii) a hyperspectral spectrometer (ASD) measured reflectance along transects during 12 day courses, (iii) spatially high resolution georeferenced hyperspectral data cubes containing the whole optical spectrum and the thermal region were gathered with an AHS sensor, and (iv) the first employment of the high performance imaging spectrometer HYPER delivered spatially explicit and multi-temporal transects across the whole region. During three measurement periods in April, June and September 2007 structural, functional and radiometric characteristics of more than 20 different vegetation types in the Les Landes region, Southwest France, were extensively characterized on the ground. The campaign concept focussed especially on quantifying plant mediated exchange processes (photosynthetic electron transport, CO2 uptake, evapotranspiration) and fluorescence emission. The comparison between passive sun-induced fluorescence and active laser-induced fluorescence was performed on a corn canopy in the daily cycle and under desiccation stress. Both techniques show good agreement in detecting stress induced fluorescence change at the 760 nm band. On the large scale, airborne and ground-level measurements of fluorescence were compared on several vegetation types supporting the scaling of this novel remote sensing signal. The multi-scale design of the four airborne radiometric measurements along with extensive ground activities fosters a nested approach to quantify photosynthetic efficiency and gross primary productivity (GPP) from passive fluorescence

Experiments with a Venue-Centric Model for Personalisedand Time-Aware Venue Suggestion

No abstract available