Transfer Learning is concerned with the application of knowledge gained from solving a problem to a different but related problem domain. In this paper, we propose a method and efficient algorithm for ranking and selecting representations from a Restricted Boltzmann Machine trained on a source domain to be transferred onto a target domain. Experiments carried out using the MNIST, ICDAR and TiCC...

Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly applied to all queries, many studies have shown that different ranking functions favour different queries, and the retrieval performance can be significantly enhanced if an appropriate ranking function is selected for each indi...

Proving the termination of a flowchart program can be done by exhibiting a ranking function, i.e., a function from the program states to a wellfounded set, which strictly decreases at each program step. A standard method to automatically generate such a function is to compute invariants for each program point and to search for a ranking in a restricted class of functions that can be handled wit...

In today’s world, internet is the main source of information. There are many blogs and forum sites available where people discuss on different issues and also almost all ecommerce website provide facility to the users to express opinion about their product and services which is important information available on the internet .The problem with this information is that this reviews are mostly not...

Web is evolving from a global information space of linked document to linked data, of which a critical source is from the structured data stored in RDB. More and more enterprises publish their RDB data into linked data and provide a simple browsing end point on it. However, this kind of browsers is usually lack of data organization and ranking, resulting in limited usability. In this paper, we ...

The Authority and Ranking Effects play a key role in data fusion. The former refers to the fact that the potential relevance of a document increases exponentially as the number of systems retrieving it increases and the latter to the phenomena that documents higher up in ranked lists and found by more systems are more likely to be relevant. Data fusion methods commonly use all the documents ret...

Document enrichment is the task of retrieving additional knowledge from external resource over what is available through source document. This task is essential because of the phenomenon that text is generally replete with gaps and ellipses since authors assume a certain amount of background knowledge. The recovery of these gaps is intuitively useful for better understanding of document. Conven...

This research addresses the need for models that guide data quality design and resource allocation decisions. Broadly, our research problem is: Given an information system that utilizes a set of data sources for producing required information, how can we determine the gain in information accuracy and, subsequently, the economic return if the accuracy of a chosen data source is improved? An earl...