Relevance feedback is a powerful technique in contentbased image retrieval (CBIR) and has been an active research area for the past few years. In this paper, we propose a new relevance feedback approach based on Bayesian classifier and it treats positive and negative feedback examples with different strategies. For positive examples, a Bayesian classifier is used to determine the distribution o...

Testable security is a key concept in FIPS 140 standards. The application of this method to non-invasive attacks is a hot topic, both for FIPS 140-3 and forthcoming ISO 17825. This paper provides insights on relevant methodologies, based on realworld case studies. Our main point is that testing divides into two tasks, namely “leakage detection” and “leakage analysis”. The first task is by far t...

This paper discusses the approximate and feedback relevant parametric identi cation of a positioning mechanism present in a wafer stepper. The positioning mechanism in a wafer stepper is used in chip manufacturing processes for accurate positioning of the silicon wafer on which the chips are to be produced. The accurate positioning requires a robust and high performance feedback controller that...

This paper reports a new document retrieval method using non-relevant documents. From a large data set of documents, we need to find documents that relate to human interesting in as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interesting. The relevance feedback needs a set of relevant ...

corrective feedback (cf) and its different types have long absorbed many scholars and practitioners. as ellis (2009) mentioned some experimental studies need to be carefully designed to discover the relative effectiveness of each of these cf techniques. the goal of this qualitative study was to discover whether the employment of different cf strategies could bring about an attitudinal shift. to...

Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the feedback information to improve the retrieval performance. This paper presents a relevance feedback scheme using Bayesian network model for feedback information adoption. Relevant images during previous iterations are ...

In interactive document retrieval, we need to find relevant documents to our interest from a large data set of documents, within a few iterations of judgement on retrieved documents. In each iteration, a comparatively small batch of documents is evaluated to establish their relevance to user’s interest. This method is also called relevance feedback, and it requires both of relevant and non-rele...

We use a retrieval system with search result clustering to tackle the NTCIR-5 WEB Query Term Expansion Subtask. The system clusters the search results in such a way as to make it easier for the user to select relevant documents as feedback documents. In addition, we select phrase words or named entities(NE) as query-expansion keywords from the feedback documents because these words tend to repr...