In this paper we describe a two-stage model for content determination in systems that summarise time series data. The first stage involves building a qualitative overview of the data set, and the second involves using this overview, together with the actual data, to produce summaries of the timeseries data. This model is based on our observations of how human experts summarise time-series data.

Building applications on databases or content management systems involves various stages such as schema design, business logic design and UI design. We explore a model driven design approach, in which the application building process is initiated by building a model. The model includes various aspects such as the data model and business rules definitions. Once the model is defined, other compon...

There is currently no model that is capable of representing the content of web resources together with their semantic web meta-data. This paper presents requirements for semantic content management, a unified human-browsable and humaneditable semantic web content model (SWCM), and its implementation swecr.

Several methods are available for mining frequent patterns in web data, but mostly they suffer from the problem of huge candidate generation and number of database scans. In view of above a genetic based model for mining frequent patterns in web content data. In the proposed genetic operator, crossing over method leads to offspring which must survive the certain fitness test or conditions to be...

It is well known that optimal server placement is NPhard. We present an approximate model of content distribution network for the case when both clients and servers are dense, and propose a simple server allocation and placement algorithm based on highrate quantization theory. The key idea is to regard the location of a request as a random variable with probability density that is proportional ...

We present the HITS submission for the 2010 TAC Guided Summarization Task. We focus on the main multi-document summarization task, rather than the update task. We implement a baseline extractive summarization system from the literature (Barzilay and Lee, 2004) which uses a Hidden Markov Model to assign sentences content or topic labels, predicts which topics most likely appear in the summary, a...

As it gets easier to add information to the web via html pages, wikis, blogs, and other documents, it gets tougher to distinguish accurate or trustworthy information from inaccurate or untrustworthy information. Moreover, apart from inaccurate or untrustworthy information, we also need to anticipate web spam – where spammers publish false facts and scams to deliberately mislead users. Creating ...

Traditional research on video data retrieval follows two general approaches. One is based on text annotation and the other on content-based comparison. However, these approaches do not fully make use of the meaning implied in a video stream. To improve these approaches, a semantic video model cooperated with a knowledge database is studied. In this paper, we propose a new semantic video model a...

The Roy model discussed here can be applied to situations where we have individuals selecting into one of two or more sectors. Examples would include, the education level choice (High School vs College) and labor participation choice (join the work force or not, especially for in the context of female labor supply). We shall examine the labor participation choice and applications of the Roy mod...

Several problems exist with traditional HMM based approaches for Web information extraction (IE) due to the lack of consideration on Web-specific features. To address this issue we present a Generalized Hidden Markov Model (GHMM) that extends HMMs by making use of Web-specific information for Web IE. In GHMM based approach, Web content blocks instead of terms are used as basic extraction unit. ...