ppxscal/embedding_network huggingface dataset:
Collaborative filtering with temporal dynamics
Authors: Yehuda Koren
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are evolving, leading them to ever redefine their taste. Thus, modeling temporal dynamics should be a key when designing recommender systems or general customer preference models. However, this raises unique challenges. Within the eco-system intersecting multiple products and customers, many different characteristics are shifting simultaneously, while many of them influence each other and often those shifts are delicate and associated with a few data instances. This distinguishes the problem from concept drift explorations, where mostly a single concept is tracked. Classical time-window or instance-decay approaches cannot work, as they lose too much signal when discarding data instances. A more sensitive approach is required, which can make better distinctions between transient effects and long term patterns. The paradigm we offer is creating a model tracking the time changing behavior throughout the life span of the data. This allows us to exploit the relevant components of all data instances, while discarding only what is modeled as being irrelevant. Accordingly, we revamp two leading collaborative filtering recommendation approaches. Evaluation is made on a large movie rating dataset by Netflix. Results are encouraging and better than those previously reported on this dataset.
Mean square asymptotic behavior of stochastic neural networks with infinitely distributed delays
Authors: Bing Li, Daoyi Xu
Venue: Neurocomputing (2009)

In this paper, according to classic M-matrix method, integral-differential inequality technique and Ito formula, we study asymptotic behavior in mean square sense of stochastic neural networks with infinitely distributed delays by establishing a generalized Halanay inequality. This is a new means for investigating asymptotic behavior of stochastic differential equation. Some useful results are derived. Especially, our methods can be extended to research p-moment asymptotic behavior easily. At last, example and simulations demonstrate the power of our methods.
Formalizing Ontology Alignment and its Operations with Category Theory
Authors: Antoine Zimmermann, Markus Krötzsch, Jérôme Euzenat, Pascal Hitzler
Venue: Proceeding of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006) (2006)

An ontology alignment is the expression of relations between different ontologies. In order to view alignments independently from the language expressing ontologies and from the techniques used for finding the alignments, we use a category-theoretical model in which ontologies are the objects. We introduce a categorical structure, called V-alignment, made of a pair of morphisms with a common domain having the ontologies as codomain. This structure serves to design an algebra that describes formally what are ontology merging, alignment composition, union and intersection using categorical constructions. This enables combining alignments of various provenance. Although the desirable properties of this algebra make such abstract manipulation of V-alignments very simple, it is practically not well fitted for expressing complex alignments: expressing subsumption between entities of two different ontologies demands the definition of non-standard categories of ontologies. We consider two approaches to solve this problem. The first one extends the notion of V-alignments to a more complex structure called W-alignments: a formalization of alignments relying on “bridge axioms.” The second one relies on an elaborate concrete category of ontologies that offers high expressive power. We show that these two extensions have different advantages that may be exploited in different contexts (viz., merging, composing, joining or meeting): the first one efficiently processes ontology merging thanks to the possible use of categorical institution theory, while the second one benefits from the simplicity of the algebra of V-alignments.
Context-oriented programming with EventJava
Authors: K. R. Jayaram, Patrick Eugster
Venue: International Workshop on Context-Oriented Programming (2009)

Recent research on Distributed Event-based Systems (DEBS) has focussed on event correlation, which is the task of processing events to identify meaningful patterns of events in the event cloud. In DEBS, software components communicate by generating, disseminating and receiving event notifications, which reify and describe the event. Several parts of an event notification are context-sensitive, depending on where the software component producing the event is deployed, the communication infrastructure available for event dissemination etc. Event contexts may be added during the production of an event (e.g. by the runtime system executing the component) or during dissemination (by a middleware) and play an integral part in event correlation. Examples of contextual information include physical time, logical time, geographical coordinates, information about the source of events, digital signatures, etc. EventJava [7], an extension of Java with advanced support for event correlation, explicitly integrates the notion of event context, thereby allowing a programmer to customize the way in which events are ordered, propagated and correlated with other events. In this paper, we explain why contexts are indispensable to DEBS, present an overview of EventJava and illustrate the use of contexts through programming examples.
Computing science: what do pupils think?
Authors: Alison Mitchell, Helen C. Purchase, John Hamer
Venue: ACM SIGCSE Bulletin (2009)

University marketing endeavours attempt to encourage school leavers to study Computing Science; the success of such attempts are becoming increasingly crucial as we see a drop in Computing Science enrollments. However, the marketing typically focusses on presenting Computing Science from the point of view of how we academics view it, with little understanding of what school pupils know of Computing Science, or their perceptions of it. We report on an extensive study into high school students' perceptions of Computing Science as a discipline, degree programme and career, and conclude that few students have a clear notion as to what Computing Science is, and that their perceptions of the discipline develop early on in their school career.
Mobility label based network: Hierarchical mobility management and packet forwarding architecture
Authors: Oleg Berzin
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

Scalability of the network layer mobility management solution is one of the most important requirements for the mobility control plane. Mobility Label Based Network (MLBN) is a new approach to the network layer mobility management problem that relies solely on MPLS to provide both macro- and micro-mobility for IPv4 and IPv6 mobile hosts and routers. This new approach does not rely on the existing IP mobility management protocols such as Mobile IP and is based on the combination of Multi-Protocol BGP (MP-BGP) and MPLS. In the context of the MLBN the scalable control plane should be capable of efficient Mobility Label distribution while allowing the MPLS-based forwarding plane to deliver mobile traffic in an optimal manner. This paper presents a hierarchical mobility management system capable of both macro- and micro-mobility support without the use of Mobile IP and its derivatives and allows scalable Mobility Label distribution and MPLS label stack based packet forwarding in support of optimal traffic delivery between the communicating mobile users.
An all-speed relaxation scheme for interface flows with surface tension
Authors: Benjamin Braconnier, Boniface Nkonga
Venue: Journal of Computational Physics (2009)

We consider interface flows where compressibility and capillary forces (surface tension) are significant. These flows are described by a non-conservative, unconditionally hyperbolic multiphase model. The numerical approximation is based on finite-volume method for unstructured grids. At the discrete level, the surface tension is approximated by a volume force (CSF formulation). The interface physical properties are recovered by designing an appropriate linearized Riemann solver (Relaxation scheme) that prevents spurious oscillations near material interfaces. For low-speed flows, a preconditioning linearization is proposed and the low Mach asymptotic is formally recovered. Numerical computations, for a bubble equilibrium, converge to the required Laplace law and the dynamic of a drop, falling under gravity, is in agreement with experimental observations.
Configuration of and Interaction Between Information Security Technologies: The Case of Firewalls and Intrusion Detection Systems
Authors: Huseyin Cavusoglu, Srinivasan Raghunathan, Hasan Cavusoglu
Venue: Information Systems Research (2009)

Proper configuration of security technologies is critical to balance the needs for access and protection of information. The common practice of using a layered security architecture that has multiple technologies amplifies the need for proper configuration because the configuration decision about one security technology has ramifications for the configuration decisions about others. Furthermore, security technologies rely on each other for their operations, thereby affecting each other's contribution. In this paper we study configuration of and interaction between a firewall and intrusion detection systems (IDS). We show that deploying a technology, whether it is the firewall or the IDS, could hurt the firm if the configuration is not optimized for the firm's environment. A more serious consequence of deploying the two technologies with suboptimal configurations is that even if the firm could benefit when each is deployed alone, the firm could be hurt by deploying both. Configuring the IDS and the firewall optimally eliminates the conflict between them, ensuring that if the firm benefits from deploying each of these technologies when deployed alone, it will always benefit from deploying both. When optimally configured, we find that these technologies complement or substitute each other. Furthermore, we find that while the optimal configuration of an IDS does not change whether it is deployed alone or together with a firewall, the optimal configuration of a firewall has a lower detection rate (i.e., allowing more access) when it is deployed with an IDS than when deployed alone. Our results highlight the complex interactions between firewall and IDS technologies when they are used together in a security architecture, and, hence, the need for proper configuration to benefit from these technologies.
Bootstrapping and evaluating named entity recognition in the biomedical domain
Authors: Andreas Vlachos, Caroline Gasperin
Venue: Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis (2006)

We demonstrate that bootstrapping a gene name recognizer for FlyBase curation from automatically annotated noisy text is more effective than fully supervised training of the recognizer on more general manually annotated biomedical text. We present a new test set for this task based on an annotation scheme which distinguishes gene names from gene mentions, enabling a more consistent annotation. Evaluating our recognizer using this test set indicates that performance on unseen genes is its main weakness. We evaluate extensions to the technique used to generate training data designed to ameliorate this problem.
Use of Landsat ETM+ data for detection of potential areas for afforestation
Authors: V. S. Bhagat
Venue: International Journal of Remote Sensing (2009)

The estimation of potential areas for afforestation (PAAs) provides the information base for planning, management and monitoring of environmental issues. A remotely sensed Landsat Enhanced Thematic Mapper Plus (ETM+) dataset was used for detection of PAAs. The existing forest densities in the study area were classified using the Normalized Difference Vegetation Index (NDVI), whereas soil moisture was based on distribution of the Soil Wetness Index (SWI). A combined map of NDVI and SWI was produced. Areas showing adequate soil moisture with inadequate/thin forest density on the combined map were considered as PAAs. Computation revealed that approximately 13% of the area under review had potential for dense afforestation, 27% for medium to dense afforestation and 53% for grasses. The methodology formulated in the present study can be used as a rapid assessment tool prior to afforestation planning.
Automatic extraction of outbreak information from news
Authors: Bing Liu
Venue:  (2008)

With the explosion of unstructured data on the Web, especially in the form of text, there has been a lot of interest to mine knowledge from these data for variety of purposes. In this thesis, we study a particular problem: how to extract disease outbreak information from news. By defining Emergent Disease Report, we focus on extracting disease name and outbreak location from the news report emergent disease outbreaks. First, we study the problem how to classify those sentences reporting disease outbreak, and propose to a new method by integrating semantic features with the bag-of-words scheme. Experimental result shows the integrated approach is better than each individual approach alone. Second, a novel method based on sequential rules is introduced to extract the outbreak locations from the outbreak reporting sentences, and the new method outperforms conditional random fields in our experimental data. Finally, we discuss how to do classification and extraction together using label sequential rules and how to geocode the extracted location named entities into geographical locations accurately. Evaluations on classification-extraction including geocoding are conducted, and the proposed method is shown to improve the overall performance.
Large-scale graph mining using backbone refinement classes
Authors: Andreas Maunz, Christoph Helma, Stefan Kramer
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum frequency and significance constraints, using classes of fragments to reduce feature set size and running times. The classes are defined in terms of fragments sharing a common backbone. The method is able to optimize structural inter-feature entropy as opposed to occurrences, which is characteristic for open or closed fragment mining. In the experiments, the proposed method reduces feature set sizes by >90 % and >30 % compared to complete tree mining and open tree mining, respectively. Evaluation using crossvalidation runs shows that their classification accuracy is similar to the complete set of trees but significantly better than that of open trees. Compared to open or closed fragment mining, a large part of the search space can be pruned due to an improved statistical constraint (dynamic upper bound adjustment), which is also confirmed in the experiments in lower running times compared to ordinary (static) upper bound pruning. Further analysis using large-scale datasets yields insight into important properties of the proposed descriptors, such as the dataset coverage and the class size represented by each descriptor. A final cross-validation run confirms that the novel descriptors render large training sets feasible which previously might have been intractable.
Collaborative and Parallelized Immersive Molecular Docking
Authors: Teeroumanee Nadan, Adrian Haffegee, Kimberly Watson
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

During docking, protein molecules and other small molecules interact together to form transient macromolecular complexes. Docking is an integral part of structure-based drug design and various docking programs are used for in-silico docking. Although these programs have powerful docking algorithms, they have limitations in the three-dimensional visualization of molecules. An immersive environment would bring additional advantages in understanding the molecules being docked. It would enable scientists to fully visualize molecules to be docked, manipulate their structures and manually dock them before sending to new conformations to a docking algorithm. This could greatly reduce docking time and resource consumption. Being an exhaustive process, parallelization of docking is of utmost importance for faster processing. This paper proposes the use of a collaborative and immersive environment for initially hand docking molecules and which then uses powerful algorithms in existing parallelized docking programs to decrease computational docking time and resources.
Forecasting New Customers' Behaviour by Means of a Fuzzy Unsupervised Method
Authors: Germán Sánchez, Juan Carlos Aguado, Núria Agell
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

The use of unsupervised fuzzy learning classi.cations techniques allows defining innovative classi.cations to be applied on marketing customer's segmentation. Segmenting the clients' portfolio in this way is important for decision-making in marketing because it allows the discovery of hidden profiles which would not be detected with other methods. Different strategies can be established for each defined segment. In this paper a case study is conducted to show the value of unsupervised fuzzy learning methods in marketing segmentation, obtaining fuzzy segmentations via the LAMDA algorithm. The use of an external decision variable related to the loyalty of the current customers will provide useful criteria to forecast potentially valuable new customers. The use of the introduced methodology should provide firms with a significant competitive edge, enabling them to design and adapt their strategies to customers' behaviour.
Relative information completeness
Authors: Wenfei Fan, Floris Geerts
Venue: Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2009)

The paper investigates the question of whether a partially closed database has complete information to answer a query. In practice an enterprise often maintains master data Dm, a closed-world database. We say that a database D is partially closed if it satisfies a set V of containment constraints of the form "q(D) is a subset of p(Dm)", where q is a query in a language Lc and p is a projection query. The part of D not constrained by (Dm,V) is open, from which some tuples may be missing. The database D is said to be complete for a query Q relative to (Dm,V) if for all partially closed extensions D' of D, Q(D')=Q(D), i.e., adding tuples to D either violates some constraints in V or does not change the answer to Q. We first show that the proposed model can also capture the consistency of data, in addition to its relative completeness. Indeed, integrity constraints studied for consistency can be expressed as containment constraints. We then study two problems. One is to decide, given Dm, V, a query Q in a language Lq and a partially closed database D, whether D is complete for Q relative to (Dm,V). The other is to determine, given Dm, V and Q, whether there exists a partially closed database that is complete for Q relative to (Dm,V). We establish matching lower and upper bounds on these problems for a variety of languages Lq and Lc. We also provide characterizations for a database to be relatively complete, and for a query to allow a relatively complete database, when Lq and Lc are conjunctive queries.
Face Video Competition
Authors: Norman Poh, Chi Ho Chan, Josef Kittler, Sébastien Marcel, Christopher Mc Cool, Enrique Argones Rúa, José Luis Castro, Mauricio Villegas, Roberto Paredes, Vitomir Štruc, Nikola Pavešić, Albert Ali Salah, Hui Fang, Nicholas Costen
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Person recognition using facial features, e.g., mug-shot images, has long been used in identity documents. However, due to the widespread use of web-cams and mobile devices embedded with a camera, it is now possible to realise facial video recognition, rather than resorting to just still images. In fact, facial video recognition offers many advantages over still image recognition; these include the potential of boosting the system accuracy and deterring spoof attacks. This paper presents the first known benchmarking effort of person identity verification using facial video data. The evaluation involves 18 systems submitted by seven academic institutes.
Recommendation system based on the clustering of frequent sets
Authors: Andrei Toma, Radu Constantinescu, Floarea Nastase
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Generating shopping recommendations has become a classical problem in knowledge engineering with extensive practical applications. In this article we propose a system for the generation of such recommendations based on considering both local and global influences.
Observation-Subsumption Checking in Similarity-Based Diagnosis of Discrete-Event Systems
Authors: Gianfranco Lamperti, Marina Zanella
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In similarity-based diagnosis of discrete-event systems the knowledge generated for solving a previous diagnostic problem can be reused to solve a new one, provided the two problems are similar. Problem-similarity requires that the temporal observation relevant to the new problem be subsumed by the temporal observation relevant to the old one. A temporal observation encompasses the (uncertain) events observed over a time interval and their (uncertain) reciprocal temporal order. Such an observation has been produced by one out of several distinct certain sequences of observable events, with each of such sequences being a sentence of the regular language of the observation. An observation subsumes another if its regular language contains the regular language of the other. However, checking observation-subsumption by following its formal definition is time consuming. In order to speed up the process, an alternative technique is proposed, which is based on the notion of coverage and exploits a number of necessary conditions, as well as a sufficient condition, for subsumption to hold. Such conditions can be directly checked on the properties of the given observations, without any need to appeal to the language theory. Experimental evidence confirms the efficiency of subsumption-checking via coverage.
Reuse of Patterns' Source Code
Authors: Jaroslav Jakubík, Pavol Návrat
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

Patterns are used in different phases of software development, from analysis through architecture, from detailed design to implementation. By using patterns, some problems are identified. One of them is how to reuse parts of patterns at the source code level. This paper is concerned with design patterns especially with reusing general parts of patterns by using different techniques and technologies. We analyze different approaches based on frameworks, libraries, CASE tools and language extensions.