104 research outputs found
Generating dynamic higher-order Markov models in web usage mining
Markov models have been widely used for modelling users’ web navigation behaviour. In previous work we have presented a dynamic clustering-based Markov model that accurately represents second-order transition probabilities given by a collection of navigation sessions. Herein, we propose a generalisation of the method that takes into account higher-order conditional probabilities. The method makes use of the state cloning concept together with a clustering technique to separate the navigation paths that reveal differences in the conditional probabilities. We report on experiments conducted with three real world data sets. The results show that some pages require a long history to understand the users choice of link, while others require only a short history. We also show that the number of additional states induced by the method can be controlled through a probability threshold parameter
Automatic Classification of Text Databases through Query Probing
Many text databases on the web are "hidden" behind search interfaces, and
their documents are only accessible through querying. Search engines typically
ignore the contents of such search-only databases. Recently, Yahoo-like
directories have started to manually organize these databases into categories
that users can browse to find these valuable resources. We propose a novel
strategy to automate the classification of search-only text databases. Our
technique starts by training a rule-based document classifier, and then uses
the classifier's rules to generate probing queries. The queries are sent to the
text databases, which are then classified based on the number of matches that
they produce for each query. We report some initial exploratory experiments
that show that our approach is promising to automatically characterize the
contents of text databases accessible on the web.Comment: 7 pages, 1 figur
Web Mining for Web Personalization
Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user\u27s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented
Ultrafast optical generation of coherent phonons in CdTe1-xSex quantum dots
We report on the impulsive generation of coherent optical phonons in
CdTe0.68Se0.32 nanocrystallites embedded in a glass matrix. Pump probe
experiments using femtosecond laser pulses were performed by tuning the laser
central energy to resonate with the absorption edge of the nanocrystals. We
identify two longitudinal optical phonons, one longitudinal acoustic phonon and
a fourth mode of a mixed longitudinal-transverse nature. The amplitude of the
optical phonons as a function of the laser central energy exhibits a resonance
that is well described by a model based on impulsive stimulated Raman
scattering. The phases of the coherent phonons reveal coupling between
different modes. At low power density excitations, the frequency of the optical
coherent phonons deviates from values obtained from spontaneous Raman
scattering. This behavior is ascribed to the presence of electronic impurity
states which modify the nanocrystal dielectric function and, thereby, the
frequency of the infrared-active phonons
Dissipative Chaos in Semiconductor Superlattices
We consider the motion of ballistic electrons in a miniband of a
semiconductor superlattice (SSL) under the influence of an external,
time-periodic electric field. We use the semi-classical balance-equation
approach which incorporates elastic and inelastic scattering (as dissipation)
and the self-consistent field generated by the electron motion. The coupling of
electrons in the miniband to the self-consistent field produces a cooperative
nonlinear oscillatory mode which, when interacting with the oscillatory
external field and the intrinsic Bloch-type oscillatory mode, can lead to
complicated dynamics, including dissipative chaos. For a range of values of the
dissipation parameters we determine the regions in the amplitude-frequency
plane of the external field in which chaos can occur. Our results suggest that
for terahertz external fields of the amplitudes achieved by present-day free
electron lasers, chaos may be observable in SSLs. We clarify the nature of this
novel nonlinear dynamics in the superlattice-external field system by exploring
analogies to the Dicke model of an ensemble of two-level atoms coupled with a
resonant cavity field and to Josephson junctions.Comment: 33 pages, 8 figure
Beyond Teaching and Learning: Bringing Together Science and Society with and through Movies
Comments on “effect of polar vibrations of the crystal lattice on the plasma frequency of heavily-doped semiconductors and correction for calculation of carrier concentration”
- …