The power of low-resolution spectroscopy: On the spectral classification of planet candidates in the ground-based CoRoT follow-up

Planetary transits detected by the CoRoT mission can be mimicked by a low-mass star in orbit around a giant star. Spectral classification helps to identify the giant stars and also early-type stars which are often excluded from further follow-up. We study the potential and the limitations of low-resolution spectroscopy to improve the photometric spectral types of CoRoT candidates. In particular, we want to study the influence of the signal-to-noise ratio (SNR) of the target spectrum in a quantitative way. We built an own template library and investigate whether a template library from the literature is able to reproduce the classifications. Including previous photometric estimates, we show how the additional spectroscopic information improves the constraints on spectral type. Low-resolution spectroscopy ($R\approx$1000) of 42 CoRoT targets covering a wide range in SNR (1-437) and of 149 templates was obtained in 2012-2013 with the Nasmyth spectrograph at the Tautenburg 2m telescope. Spectral types have been derived automatically by comparing with the observed template spectra. The classification has been repeated with the external CFLIB library. The spectral class obtained with the external library agrees within a few sub-classes when the target spectrum has a SNR of about 100 at least. While the photometric spectral type can deviate by an entire spectral class, the photometric luminosity classification is as close as a spectroscopic classification with the external library. A low SNR of the target spectrum limits the attainable accuracy of classification more strongly than the use of external templates or photometry. Furthermore we found that low-resolution reconnaissance spectroscopy ensures that good planet candidates are kept that would otherwise be discarded based on photometric spectral type alone.Comment: accepted for publication in Astronomische Nachrichten; 12 pages, 4 figures, 7 table

Web 2.0 and folksonomies in a library context

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 ElsevierLibraries have a societal purpose and this role has become increasingly important as new technologies enable organizations to support, enable and enhance the participation of users in assuming an active role in the creation and communication of information. Folksonomies, a Web 2.0 technology, represent such an example. Folksonomies result from individuals freely tagging resources available to them on a computer network. In a library environment folksonomies have the potential of overcoming certain limitations of traditional classification systems such as the Library of Congress Subject Headings (LCSH). Typical limitations of this type of classification systems include, for example, the rigidity of the underlying taxonomical structures and the difficulty of introducing change in the categories. Folksonomies represent a supporting technology to existing classification systems helping to describe library resources more flexibly, dynamically and openly. As a review of the current literature shows, the adoption of folksonomies in libraries is novel and limited research has been carried out in the area. This paper presents research into the adoption of folksonomies for a University library. A Web 2.0 system was developed, based on the requirements collected from library stakeholders, and integrated with the existing library computer system. An evaluation of the work was carried out in the form of a survey in order to understand the possible reactions of users to folksonomies as well as the effects on their behavior. The broad conclusion of this work is that folksonomies seem to have a beneficial effect on users’ involvement as active library participants as well as encourage users to browse the catalogue in more depth

Concept Extraction and Clustering for Topic Digital Library Construction

This paper is to introduce a new approach to build topic digital library using concept extraction and document clustering. Firstly, documents in a special domain are automatically produced by document classification approach. Then, the keywords of each document are extracted using the machine learning approach. The keywords are used to cluster the documents subset. The clustered result is the taxonomy of the subset. Lastly, the taxonomy is modified to the hierarchical structure for user navigation by manual adjustments. The topic digital library is constructed after combining the full-text retrieval and hierarchical navigation function

Feature Selection Library (MATLAB Toolbox)

Feature Selection Library (FSLib) is a widely applicable MATLAB library for Feature Selection (FS). FS is an essential component of machine learning and data mining which has been studied for many years under many different conditions and in diverse scenarios. These algorithms aim at ranking and selecting a subset of relevant features according to their degrees of relevance, preference, or importance as defined in a specific application. Because feature selection can reduce the amount of features used for training classification models, it alleviates the effect of the curse of dimensionality, speeds up the learning process, improves model's performance, and enhances data understanding. This short report provides an overview of the feature selection algorithms included in the FSLib MATLAB toolbox among filter, embedded, and wrappers methods.Comment: Feature Selection Library (FSLib) 201

Two-dimensional ranking of Wikipedia articles

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists {\it ab aeterno}. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.Comment: RevTex 9 pages, data, discussion added, more data at http://www.quantware.ups-tlse.fr/QWLIB/2drankwikipedia

The Role of Indexing in Subject Retrieval

On first reading the list of speakers proposed for this institute, I became aware of being rather the "odd man out" for two reasons. Firstly, I was asked to present a paper on PRECIS which is very much a verbal indexing system-at a conference dominated by contributions on classification schemes with a natural bias, as the centenary year approaches, toward the Dewey Decimal Classification (DDC). Secondly, I feared (quite wrongly, as it happens) that I might be at variance with one or two of my fellow speakers, who would possibly like to assure us, in an age when we can no longer ignore the computer, that traditional library schemes such as DDC and Library of Congress Classification (LCC) are capable of maintaining their original function of organizing collections of documents, and at the same time are also well suited to the retrieval of relevant citations from machine-held files. In this context, I am reminded of a review of a general collection of essays on classification schemes which appeared in the Journal of Documentation in 1972. Norman Roberts, reviewing the papers which dealt specifically with the well established schemes, deduced that "all the writers project their particular schemes into the future with an optimism that springs, perhaps, as much from a sense of emotional involvement as from concrete evidence." Since I do not believe that these general schemes can play any significant part in the retrieval of items from mechanized files, it appeared that I had been cast in the role of devil's advocate.published or submitted for publicatio