Internship report: improving asymmetric term extraction from bilingual text

Estudi elaborat a partir d’una estada a Xerox Research Centre Europe a Grenoble, França,entre juny i desembre del 2006. El projecte tradueïx termes tècnics anglesos a noruec. És asimètric perquè no tenim recursos lingüístics per a la llengua noruega, però solament per a l'anglès. S’ha desenvolupat i posat en pràctica mètodes que comprovaven contigüitat ("local reordering" i permutació selectiva) per a millorar el funcionament d’una eina anterior. Contigüitat és quan una paraula es traduïx en paraules múltiples, aquestes paraules han de ser adjacents en l'oració. A més, s’ha construït una taula de les operacions de recerca per als termes tècnics i s’ha integrat aquesta taula en un programa de demostració.

Merging the hypothetical extraction method and the classical multiplier approach: a hybrid possibility for identifying key distributive sectors

The two main alternative methods used to identify key sectors within the input-output approach, the Classical Multiplier method (CMM) and the Hypothetical Extraction method (HEM), are formally and empirically compared in this paper. Our findings indicate that the main distinction between the two approaches stems from the role of the internal effects. These internal effects are quantified under the CMM while under the HEM only external impacts are considered. In our comparison, we find, however that CMM backward measures are more influenced by within-block effects than the proposed forward indices under this approach. The conclusions of this comparison allow us to develop a hybrid proposal that combines these two existing approaches. This hybrid model has the advantage of making it possible to distinguish and disaggregate external effects from those that a purely internal. This proposal has also an additional interest in terms of policy implications. Indeed, the hybrid approach may provide useful information for the design of ''second best'' stimulus policies that aim at a more balanced perspective between overall economy-wide impacts and their sectoral distribution.

A unified approach for representing rows and columns in contingency tables

By using suitable parameters, we present a uni¯ed aproach for describing four methods for representing categorical data in a contingency table. These methods include:correspondence analysis (CA), the alternative approach using Hellinger distance (HD),the log-ratio (LR) alternative, which is appropriate for compositional data, and theso-called non-symmetrical correspondence analysis (NSCA). We then make an appropriate comparison among these four methods and some illustrative examples are given.Some approaches based on cumulative frequencies are also linked and studied usingmatrices.Key words: Correspondence analysis, Hellinger distance, Non-symmetrical correspondence analysis, log-ratio analysis, Taguchi inertia

Analysis and evaluation of techniques for the extraction of classes in the ontology learning process

This paper analyzes and evaluates, in the context of Ontology learning, some techniques to identify and extract candidate terms to classes of a taxonomy. Besides, this work points out some inconsistencies that may be occurring in the preprocessing of text corpus, and proposes techniques to obtain good terms candidate to classes of a taxonomy.

Definitional verbal patterns for semantic relation extraction

In this paper we present a description of the role of definitional verbal patterns for the extraction of semantic relations. Several studies show that semantic relations can be extracted from analytic definitions contained in machine-readable dictionaries (MRDs). In addition, definitions found in specialised texts are a good starting point to search for different types of definitions where other semantic relations occur. The extraction of definitional knowledge from specialised corpora represents another interesting approach for the extraction of semantic relations. Here, we present a descriptive analysis of definitional verbal patterns in Spanish and the first steps towards the development of a system for the automatic extraction of definitional knowledge.

Automatic Extraction of Polar Adjectives for the Creation of Polarity Lexicons

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time andefforts in the first steps of Sentiment Analysis. In this paper we present a methodology based onlinguistic cues that allows us to automatically discover, extract and label subjective adjectivesthat should be collected in a domain-based polarity lexicon. For this purpose, we designed abootstrapping algorithm that, from a small set of seed polar adjectives, is capable to iterativelyidentify, extract and annotate positive and negative adjectives. Additionally, the methodautomatically creates lists of highly subjective elements that change their prior polarity evenwithin the same domain. The algorithm proposed reached a precision of 97.5% for positiveadjectives and 71.4% for negative ones in the semantic orientation identification task.

Semantic web adoption: online tools for web evaluation and metadata extraction

This work briefly analyses the difficulties to adopt the Semantic Web, and in particular proposes systems to know the present level of migration to the different technologies that make up the Semantic Web. It focuses on the presentation and description of two tools, DigiDocSpider and DigiDocMetaEdit, designed with the aim of verifYing, evaluating, and promoting its implementation.

Monetary policy with signal extraction from the bond market

Monetary policy is conducted in an environment of uncertainty. This paper sets upa model where the central bank uses real-time data from the bond market togetherwith standard macroeconomic indicators to estimate the current state of theeconomy more efficiently, while taking into account that its own actions influencewhat it observes. The timeliness of bond market data allows for quicker responsesof monetary policy to disturbances compared to the case when the central bankhas to rely solely on collected aggregate data. The information content of theterm structure creates a link between the bond market and the macroeconomythat is novel to the literature. To quantify the importance of the bond market asa source of information, the model is estimated on data for the United Statesand Australia using Bayesian methods. The empirical exercise suggests that thereis some information in the US term structure that helps the Federal Reserve toidentify shocks to the economy on a timely basis. Australian bond prices seemto be less informative than their US counterparts, perhaps because Australia is arelatively small and open economy.

Audit risk and rent extraction: Evidence from a randomized evaluation in Brazil

We report results from a randomized policy experiment designed to test whether increasedaudit risk deters rent extraction in local public procurement and service delivery in Brazil. Ourestimates suggest that temporarily increasing annual audit risk by about 20 percentage pointsreduced the proportion of irregular local procurement processes by about 17 percentage points.This reduction was driven entirely by irregularities involving mismanagement or corruption. Incontrast, we find no evidence that increased audit risk affected the quality of publicly providedpreventive and primary health care services -measured based on user satisfaction surveys- orcompliance with national regulations of the conditional cash transfer program "Bolsa Família".

Judicial presence and rent extraction

We estimate the effect of state judiciary presence on rent extraction in Brazilian local governments.We measure rents as irregularities related to waste or corruption uncovered by auditors.Our unique dataset at the level of individual inspections allows us to separately examine extensiveand intensive margins of rent extraction. The identification strategy is based on an institutionalrule of state judiciary branches according to which prosecutors and judges tend to be assigned tothe most populous among contiguous counties forming a judiciary district. Our research designexploits this rule by comparing counties that are largest in their district to counties with identicalpopulation size from other districts in the same state, where they are not the most populous. IVestimates suggest that state judiciary presence reduces the share of inspections with irregularitiesrelated to waste or corruption by about 10 percent or 0.3 standard deviations. In contrast, we findno effect on the intensive margin of rent extraction. Finally, our estimates suggest that judicialpresence reduces rent extraction only for first-term mayors.

Simple and fast methods based on solid-phase extraction coupled to liquid chromatography with UV detection for the monitoring of caffeine in natural and waste waters as marker of anthropogenic impact

Two concentration methods for fast and routine determination of caffeine (using HPLC-UV detection) in surface, and wastewater are evaluated. Both methods are based on solid-phase extraction (SPE) concentration with octadecyl silica sorbents. A common “offline” SPE procedure shows that quantitative recovery of caffeine is obtained with 2 mL of an elution mixture solvent methanol-water containing at least 60% methanol. The method detection limit is 0.1 μg L−1 when percolating 1 L samples through the cartridge. The development of an “online” SPE method based on a mini-SPE column, containing 100 mg of the same sorbent, directly connected to the HPLC system allows the method detection limit to be decreased to 10 ng L−1 with a sample volume of 100 mL. The “offline” SPE method is applied to the analysis of caffeine in wastewater samples, whereas the “on-line” method is used for analysis in natural waters from streams receiving significant water intakes from local wastewater treatment plants

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals

Background: oscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies. Oscillatory burst events should consequently play a specific functional role, distinct from background EEG activity – especially for cognitive tasks (e.g. working memory tasks), binding mechanisms and perceptual dynamics (e.g. visual binding), or in clinical contexts (e.g. effects of brain disorders). However extracting oscillatory events in single trials, with a reliable and consistent method, is not a simple task. Results: in this work we propose a user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals. The software is provided with a Matlab toolbox which can compute wavelet representations before calling automatically the stand-alone application. Conclusion: The tool is publicly available as a freeware at the address: http:// www.bsp.brain.riken.jp/bumptoolbox/toolbox_home.html

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.