35,256 research outputs found
Special Libraries, March 1970
Volume 61, Issue 3https://scholarworks.sjsu.edu/sla_sl_1970/1002/thumbnail.jp
Special Libraries, July 1978
Volume 69, Issue 7https://scholarworks.sjsu.edu/sla_sl_1978/1005/thumbnail.jp
A new metric for patent retrieval evaluation
Patent retrieval is generally considered to be a recall-oriented information retrieval task that is growing in importance. Despite this fact, precision based scores such as mean average precision (MAP) remain the primary evaluation measures for patent retrieval. Our study examines different evaluation measures for the recall-oriented patent retrieval task and shows the limitations
of the current scores in comparing different IR systems for this task. We introduce PRES, a novel evaluation metric for this type of application taking account of recall and user search effort. The behaviour of PRES is demonstrated on 48 runs from the CLEF-IP 2009 patent retrieval track. A full analysis of the performance of PRES shows its suitability for measuring the retrieval effectiveness of systems from a recall focused perspective taking into account the expected search effort of patent searchers
PRES: A score metric for evaluating recall-oriented information retrieval applications
Information retrieval (IR) evaluation scores are generally
designed to measure the effectiveness with which relevant
documents are identified and retrieved. Many scores have been proposed for this purpose over the years. These have primarily focused on aspects of precision and recall, and while these are often discussed with equal importance, in practice most attention has been given to precision focused metrics. Even for recalloriented IR tasks of growing importance, such as patent retrieval, these precision based scores remain the primary evaluation measures. Our study examines different evaluation measures for a recall-oriented patent retrieval task and demonstrates the limitations of the current scores in comparing different IR systems for this task. We introduce PRES, a novel evaluation metric for this type of application taking account of recall and the user’s search effort. The behaviour of PRES is demonstrated on 48 runs from the CLEF-IP 2009 patent retrieval track. A full analysis of the performance of PRES shows its suitability for measuring the
retrieval effectiveness of systems from a recall focused
perspective taking into account the user’s expected search effort
Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine
Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)
Atmospheric Retrieval for Super-Earths: Uniquely Constraining the Atmospheric Composition with Transmission Spectroscopy
We present a retrieval method based on Bayesian analysis to infer the
atmospheric compositions and surface or cloud-top pressures from transmission
spectra of exoplanets with general compositions. In this study, we identify
what can unambiguously be determined about the atmospheres of exoplanets from
their transmission spectra by applying the retrieval method to synthetic
observations of the super-Earth GJ 1214b. Our approach to infer constraints on
atmospheric parameters is to compute their joint and marginal posterior
probability distributions using the MCMC technique in a parallel tempering
scheme. A new atmospheric parameterization is introduced that is applicable to
general atmospheres in which the main constituent is not known a priori and
clouds may be present. Our main finding is that a unique constraint of the
mixing ratios of the absorbers and up to two spectrally inactive gases (such as
N2 and primordial H2+He) is possible if the observations are sufficient to
quantify both (1) the broadband transit depths in at least one absorption
feature for each absorber and (2) the slope and strength of the molecular
Rayleigh scattering signature. The surface or cloud-top pressure can be
quantified if a surface or cloud deck is present. The mean molecular mass can
be constrained from the Rayleigh slope or the shapes of absorption features,
thus enabling to distinguish between cloudy hydrogen-rich atmospheres and high
mean molecular mass atmospheres. We conclude, however, that without the
signature of Rayleigh scattering--even with robustly detected infrared
absorption features--there is no reliable way to tell if the absorber is the
main constituent of the atmosphere or just a minor species with a mixing ratio
of <0.1%. The retrieval method leads us to a conceptual picture of which
details in transmission spectra are essential for unique characterizations of
well-mixed atmospheres.Comment: 23 pages, 13 figures, accepted at ApJ, submitted to ApJ on Nov 4,
201
BoWFire: Detection of Fire in Still Images by Integrating Pixel Color and Texture Analysis
Emergency events involving fire are potentially harmful, demanding a fast and
precise decision making. The use of crowdsourcing image and videos on crisis
management systems can aid in these situations by providing more information
than verbal/textual descriptions. Due to the usual high volume of data,
automatic solutions need to discard non-relevant content without losing
relevant information. There are several methods for fire detection on video
using color-based models. However, they are not adequate for still image
processing, because they can suffer on high false-positive results. These
methods also suffer from parameters with little physical meaning, which makes
fine tuning a difficult task. In this context, we propose a novel fire
detection method for still images that uses classification based on color
features combined with texture classification on superpixel regions. Our method
uses a reduced number of parameters if compared to previous works, easing the
process of fine tuning the method. Results show the effectiveness of our method
of reducing false-positives while its precision remains compatible with the
state-of-the-art methods.Comment: 8 pages, Proceedings of the 28th SIBGRAPI Conference on Graphics,
Patterns and Images, IEEE Pres
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