Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

An intelligent electronic appliance preferably includes a user interface, data input and/or output port, and an intelligent processor. A preferred embodiment comprises a set top box for interacting with broadband media streams, with an adaptive user interface, content-based media processing and/or media metadata processing, and telecommunications integration. An adaptive user interface models the user, by observation, feedback, and/or explicit input, and presents a user interface and/or executes functions based on the user model. A content-based media processing system analyzes media content, for example audio and video, to understand the content, for example to generate content-descriptive metadata. A media metadata processing system operates on locally or remotely generated metadata to process the media in accordance with the metadata, which may be, for example, an electronic program guide, MPEG 7 data, and/or automatically generated format. A set top box preferably includes digital trick play effects, and incorporated digital rights management features.

Intelligent electronic appliance system and method

Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behaviour accordingly. Especially in combination with mobile devices, these mechanisms are of high value and are used to increase usability tremendously. In this paper, we present common architecture principles of context-aware systems and derive a layered conceptual design framework to explain the different elements common to most context-aware architectures. Based on these design principles, we introduce various existing context-aware systems focusing on context-aware middleware and frameworks, which ease the development of context-aware applications. We discuss various approaches and analyse important aspects in context-aware computing on the basis of the presented systems.

/pdf/a-survey-on-context-aware-systems-47xtrbjsqu.pdf

A survey on context-aware systems

We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

http://www.cs.man.ac.uk/~horrocks/Publications/download/2003/HoPH03a.pdf

From SHIQ and RDF to OWL: the making of a Web Ontology Language

Universality, the property of the Web that makes it the largest data and information source in the world, is also the property behind the lack of a uniform organization scheme that would allow easy access to data and information. A semantic web, wherein different applications and Web sites can exchange information and hence exploit Web data and information to their full potential, requires the information about Web resources to be represented in a detailed and structured manner. Resource Description Framework (RDF), an effort in this direction supported by the World Wide Web Consortium, provides a means for the description of metadata which is a necessity for the next generation of interoperable Web applications. The success of RDF and the semantic web will depend on (1) the development of applications that prove the applicability of the concept, (2) the availability of application interfaces which enable the development of such applications, and (3) databases and inference systems that exploit RDF to identify and locate most relevant Web resources. In addition, many practical issues, such as security, ease of use, and compatibility, will be crucial in the success of RDF. This survey aims at providing a glimpse at the past, present, and future of this upcoming technology and highlights why we believe that the next generation of the Web will be more organized, informative, searchable, accessible, and, most importantly, useful. It is expected that knowledge discovery and data mining can benefit from RDF and the Semantic Web.

Resource description framework: metadata and its applications

Platforms such as Twitter have provided researchers with ample opportunities to analytically study social phenomena. There are however, significant computational challenges due to the enormous rate of production of new information: researchers are therefore, often forced to analyze a judiciously selected “sample” of the data. Like other social media phenomena, information diffusion is a social process–it is affected by user context, and topic, in addition to the graph topology. This paper studies the impact of different attribute and topology based sampling strategies on the discovery of an important social media phenomena–information diffusion. We examine several widely-adopted sampling methods that select nodes based on attribute (random, location, and activity) and topology (forest fire) as well as study the impact of attribute based seed selection on topology based sampling. Then we develop a series of metrics for evaluating the quality of the sample, based on user activity (e.g. volume, number of seeds), topological (e.g. reach, spread) and temporal characteristics (e.g. rate). We additionally correlate the diffusion volume metric with two external variables–search and news trends. Our experiments reveal that for small sample sizes (30%), a sample that incorporates both topology and user context (e.g. location, activity) can improve on naive methods by a significant margin of ~15-20%.

/pdf/how-does-the-data-sampling-strategy-impact-the-discovery-of-5ew5uvq2gv.pdf

How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media

Tree pattern matching is one of the most fundamental tasks for XML query processing. Holistic twig query processing techniques [4, 16] have been developed to minimize the intermediate results, namely, those root-to-leaf path matches that are not in the final twig results. However, useless path matches cannot be completely avoided, especially when there is a parent-child relationship in the twig query. Furthermore, existing approaches do not consider the fact that in practice, in order to process XPath or XQuery statements, a more powerful form of twig queries, namely, Generalized-Tree-Pattern (GTP) [8] queries, is required. Most existing works on processing GTP queries generally calls for costly post-processing for eliminating redundant data and/or grouping of the matching results.In this paper, we first propose a novel hierarchical stack encoding scheme to compactly represent the twig results. We introduce Twig2Stack, a bottom-up algorithm for processing twig queries based on this encoding scheme. Then we show how to efficiently enumerate the query results from the encodings for a given GTP query. To our knowledge, this is the first GTP matching solution that avoids any post path-join, sort, duplicate elimination and grouping operations. Extensive performance studies on various data sets and queries show that the proposed Twig2Stack algorithm not only has better twig query processing performance than state-of-the-art algorithms, but is also capable of efficiently processing the more complex GTP queries.

/pdf/twig2stack-bottom-up-processing-of-generalized-tree-pattern-50kx4xh50g.pdf

Twig2Stack: bottom-up processing of generalized-tree-pattern queries over XML documents

A method and apparatus for verifying a query to provide feedback to users for query reformulation. By utilizing selectivity statistics for semantic and visual characteristics of image objects, query verification “examines” user queries and allows users to reformulate queries through system feedback. Feedback information provided to the user includes (1) the maximum and minimum number of matches for the query; (2) alternatives for both semantic and visual-based query elements; and (3) estimated numbers of matching images. Additional types of feedback information may also be provided. With this feedback, the users know if the query criteria is too tight (i.e. too few matches will be retrieved) or too loose (i.e. too many matches will be retrieved) so that they can relax, refine, or reformulate queries or leave queries unchanged accordingly. Only after queries are verified to have a high possibility of meaningful results, are the queries processed. Through this type of systematic feedback, users can query and explore multimedia databases, for example, by honing in on target images without expensive query processing. This provides a reduction in expensive query processing and system load.

Method and apparatus for facilitating query reformulation

Web performance is a key differentiation among content providers. Snafus and slowdowns at major web sites demonstrate the difficulty that companies face trying to scale to a large amount of web traffic. One solution to this problem is to store web content at server-side and edge-caches for fast delivery to the end users. However, for many e-commerce sites, web pages are created dynamically based on the current state of business processes, represented in application servers and databases. Since application servers, databases, web servers, and caches are independent components, there is no efficient mechanism to make changes in the database content reflected to the cached web pages. As a result, most application servers have to mark dynamically generated web pages as non-cacheable. In this paper, we describe the architectural framework of the CachePortal system for enabling dynamic content caching for database-driven e-commerce sites. We describe techniques for intelligently invalidating dynamically generated web pages in the caches, thereby enabling caching of web pages generated based on database contents. We use some of the most popular components in the industry to illustrate the deployment and applicability of the proposed architecture.

https://www.public.asu.edu/~candan/papers/sigmod01.pdf

K. Selçuk Candan

Papers

Resource description framework: metadata and its applications

How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media

Twig2Stack: bottom-up processing of generalized-tree-pattern queries over XML documents

Method and apparatus for facilitating query reformulation

Enabling dynamic content caching for database-driven web sites