Enhancing new user cold-start based on decision trees active learning by using past warm-users predictions

The cold-start is the situation in which the recommender system has no or not enough information about the (new) users/items, i.e. their ratings/feedback; hence, the recommendations are not accurate. Active learning techniques for recommender systems propose to interact with new users by asking them to rate sequentially a few items while the system tries to detect her preferences. This bootstraps recommender systems and alleviate the new user cold-start. Compared to current state of the art, the presented approach takes into account the users' ratings predictions in addition to the available users' ratings. The experimentation shows that our approach achieves better performance in terms of precision and limits the number of questions asked to the users

An item/user representation for recommender systems based on bloom filters

This paper focuses on the items/users representation in the domain of recommender systems. These systems compute similarities between items (and/or users) to recommend new items to users based on their previous preferences. It is often useful to consider the characteristics (a.k.a features or attributes) of the items and/or users. This represents items/users by vectors that can be very large, sparse and space-consuming. In this paper, we propose a new accurate method for representing items/users with low size data structures that relies on two concepts: (1) item/user representation is based on bloom filter vectors, and (2) the usage of these filters to compute bitwise AND similarities and bitwise XNOR similarities. This work is motivated by three ideas: (1) detailed vector representations are large and sparse, (2) comparing more features of items/users may achieve better accuracy for items similarities, and (3) similarities are not only in common existing aspects, but also in common missing aspects. We have experimented this approach on the publicly available MovieLens dataset. The results show a good performance in comparison with existing approaches such as standard vector representation and Singular Value Decomposition (SVD)

Vortical and Wave Modes in 3D Rotating Stratified Flows: Random Large Scale Forcing

Utilizing an eigenfunction decomposition, we study the growth and spectra of energy in the vortical and wave modes of a 3D rotating stratified fluid as a function of $\epsilon = f/N$. Working in regimes characterized by moderate Burger numbers, i.e. $Bu = 1/\epsilon^2 < 1$ or $Bu \ge 1$, our results indicate profound change in the character of vortical and wave mode interactions with respect to $Bu = 1$. As with the reference state of $\epsilon=1$, for $\epsilon < 1$ the wave mode energy saturates quite quickly and the ensuing forward cascade continues to act as an efficient means of dissipating ageostrophic energy. Further, these saturated spectra steepen as $\epsilon$ decreases: we see a shift from $k^{-1}$ to $k^{-5/3}$ scaling for $k_f < k < k_d$ (where $k_f$ and $k_d$ are the forcing and dissipation scales, respectively). On the other hand, when $\epsilon > 1$ the wave mode energy never saturates and comes to dominate the total energy in the system. In fact, in a sense the wave modes behave in an asymmetric manner about $\epsilon = 1$. With regard to the vortical modes, for $\epsilon \le 1$, the signatures of 3D quasigeostrophy are clearly evident. Specifically, we see a $k^{-3}$ scaling for $k_f < k < k_d$ and, in accord with an inverse transfer of energy, the vortical mode energy never saturates but rather increases for all $k < k_f$. In contrast, for $\epsilon > 1$ and increasing, the vortical modes contain a progressively smaller fraction of the total energy indicating that the 3D quasigeostrophic subsystem plays an energetically smaller role in the overall dynamics.Comment: 18 pages, 6 figs. (abbreviated abstract

Non-Gaussian Distributions in Extended Dynamical Systems

We propose a novel mechanism for the origin of non-Gaussian tails in the probability distribution functions (PDFs) of local variables in nonlinear, diffusive, dynamical systems including passive scalars advected by chaotic velocity fields. Intermittent fluctuations on appropriate time scales in the amplitude of the (chaotic) noise can lead to exponential tails. We provide numerical evidence for such behavior in deterministic, discrete-time passive scalar models. Different possibilities for PDFs are also outlined.Comment: 12 pages and 6 figs obtainable from the authors, LaTex file, OSU-preprint-

Simplifying syntactic and semantic parsing of NL-based queries in advanced application domains

The paper presents a high level query language (MDDQL) for databases, which relies on an ontology driven automaton. This is simulated by the human-computer interaction mode for the query construction process, which is driven by an inference engine operating upon a frames based ontology description. Therefore, given that the query construction process implicitly leads to the contemporary construction of high level query trees prior to submission of the query for transformation and execution to a semantic middle-ware, syntactic and semantic parsing of a query with conventional techniques, i.e., after completion of its formulation, becomes obsolete. To this extent, only, as meaningful as possible, queries can be constructed at a low typing, learning, syntactic and semantic parsing effort and regardless the preferred natural (sub)language. From a linguistics point o view, it turns out that the query construction mechanism can easily be adapted and work with families of natural languages, which underlie another type order such as Subject-Object-Verb as opposed to the typical Subject-Verb-Object type order, which underlie most European languages. The query construction mechanism has been proved as practical in advanced application domains, such as those provided by medical applications, with an advanced and hardly understood terminology for naive users and the public

BCL2A1a Over-Expression in Murine Hematopoietic Stem and Progenitor Cells Decreases Apoptosis and Results in Hematopoietic Transformation

We previously reported the development of a lethal myeloid sarcoma in a non-human primate model utilizing retroviral vectors to genetically modify hematopoietic stem and progenitor cells. This leukemia was characterized by insertion of the vector provirus into the BCL2A1 gene, with resultant BCL2A1 over-expression. There is little information on the role of this anti-apoptotic member of the BCL2 family in hematopoiesis or leukemia induction. Therefore we studied the impact of Bcl2a1a lentiviral over-expression on murine hematopoietic stem and progenitor cells. We demonstrated the anti-apoptotic function of this protein in hematopoietic cells, but did not detect any impact of Bcl2a1a on in vitro cell growth or cell cycle kinetics. In vivo, we showed a higher propensity of HSCs over-expressing Bcl2a1a to engraft and contribute to hematopoiesis. Mice over-expressing Bcl2a1a in the hematologic compartment eventually developed an aggressive malignant disease characterized as a leukemia/lymphoma of B-cell origin. Secondary transplants carried out to investigate the primitive origin of the disease revealed the leukemia was transplantable. Thus, Bcl2a1 should be considered as a protooncogene with a potential role in both lymphoid and myeloid leukemogenesis, and a concerning site for insertional activation by integrating retroviral vectors utilized in hematopoietic stem cell gene therapy.intramural research programs of the National Heart Lung and Blood Institute (CED) of the National Institutes of Healthintramural research programs of the National Heart Lung and Blood Institute (CED) of the National Institutes of Healt

DomPep—A General Method for Predicting Modular Domain-Mediated Protein-Protein Interactions

Protein-protein interactions (PPIs) are frequently mediated by the binding of a modular domain in one protein to a short, linear peptide motif in its partner. The advent of proteomic methods such as peptide and protein arrays has led to the accumulation of a wealth of interaction data for modular interaction domains. Although several computational programs have been developed to predict modular domain-mediated PPI events, they are often restricted to a given domain type. We describe DomPep, a method that can potentially be used to predict PPIs mediated by any modular domains. DomPep combines proteomic data with sequence information to achieve high accuracy and high coverage in PPI prediction. Proteomic binding data were employed to determine a simple yet novel parameter Ligand-Binding Similarity which, in turn, is used to calibrate Domain Sequence Identity and Position-Weighted-Matrix distance, two parameters that are used in constructing prediction models. Moreover, DomPep can be used to predict PPIs for both domains with experimental binding data and those without. Using the PDZ and SH2 domain families as test cases, we show that DomPep can predict PPIs with accuracies superior to existing methods. To evaluate DomPep as a discovery tool, we deployed DomPep to identify interactions mediated by three human PDZ domains. Subsequent in-solution binding assays validated the high accuracy of DomPep in predicting authentic PPIs at the proteome scale. Because DomPep makes use of only interaction data and the primary sequence of a domain, it can be readily expanded to include other types of modular domains

Channel like 3D seismic feature in carbonate platform : incised valley or tidal channel ? Some geometric characterisations provided by outcrops and modern environment

Boichard R., Metais E., Machhour Louaï. Channel like 3D seismic feature in carbonate platform : incised valley or tidal channel ? Some geometric characterisations provided by outcrops and modern environment. In: Géologie Méditerranéenne. Tome 28, numéro 1-2, 2001. Anatomy of Carbonate Bodies / Anatomie des corps carbonates. International Meeting / Colloque international. Marseille, 9-12 mai 2001, France, sous la direction de Marc Floquet, Jérôme Hennuy et Jean-Pierre Masse. pp. 19-22

Application of natural language to information systems (NLDB'14)

International audienceThis special issue consists of four revised and extended papers selected from the 19th International conference on Applications of Natural Language to Information Systems (NLDB 2014), which was organized in June 2014 in Montpellier, France. For nearly 20 years, NLDB conferences (http://nldb.org) bring together researchers interested in the use of natural language processing techniques in applications such as database querying, information systems architecture, software development, specification checking, and more recently, various applications dealing with automatic enrichment of and advanced search in large volumes of web content, including opinion mining and sentiment analysis. Authors of a selected number of contributions to the conference (13 full papers, 8 short papers, and 14 poster presentations, among the 73 submitted ones) were asked to develop their papers into journal articles. After additional reviewing, 4 papers were eventually selected for this special issue. The addressed topics (e.g, information retrieval, information extraction, reasoning, disambiguation) underline the various and complex issues addressed by the Natural Language Processing (NLP) and Information Systems (IS) communities