257 research outputs found
A fine grained heuristic to capture web navigation patterns
In previous work we have proposed a statistical model to capture the user behaviour when browsing the web. The user navigation information obtained from web logs is modelled as a hypertext probabilistic grammar (HPG) which
is within the class of regular probabilistic grammars. The set of highest probability strings generated by the grammar corresponds to the user preferred navigation trails. We have previously conducted experiments with a Breadth-First Search algorithm (BFS) to perform the exhaustive computation of all the strings with probability above a specified cut-point, which we call the rules. Although the algorithm’s running time varies linearly with the number of grammar states, it has the drawbacks of returning a large number of rules when the cut-point is small and a small set of very short rules when the cut-point is high.
In this work, we present a new heuristic that implements an iterative deepening search wherein the set of rules is incrementally augmented by first exploring trails with high probability. A stopping parameter is provided which measures the distance between the current rule-set and its corresponding maximal set obtained by the BFS algorithm. When the stopping parameter takes the value zero the heuristic corresponds to the BFS algorithm and as the parameter takes
values closer to one the number of rules obtained decreases accordingly.
Experiments were conducted with both real and synthetic data and the results show that for a given cut-point the number of rules induced increases smoothly with the decrease of the stopping criterion. Therefore, by setting the value of the stopping criterion the analyst can determine the number and quality of rules to be induced; the quality of a rule is measured by both its length and probability
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
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Connecting on Climate: A Guide to Effective Climate Change Communication
Climate change is not a new issue, but the need for meaningful and sustainable solutions is more urgent than ever. Climate communicators and mainstream leaders are still grappling with how to help Americans find meaningful, actionable paths forward and overcome the social, political, psychological, and emotional barriers that have hindered progress on climate solutions.
To connect with audiences and unlock success in climate change communication, communicators need to shift their approach. Communicators need to go beyond simply providing people with the facts about climate change. They need to connect with people’s values and worldviews and put solutions at the forefront to make climate change personally relevant to Americans and those they love.
With this guide, we have brought together both researchers and practitioners to consolidate the best insights and evidence about how to communicate effectively about climate change. We have combined research from the Center for Research on Environmental Decisions (CRED) at The Earth Institute, Columbia University; ecoAmerica; and other institutions with insights that ecoAmerica has gleaned from communicating about climate change and other environmental issues with mainstream Americans and their leaders. This guide presents information in a digestible, actionable form to enable communicators to “up their game” when engaging Americans on climate solutions of all types and scales
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
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