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Following the trend of big data, the business value of data is becoming a hot research field in recent years. The novel concept of Data Jacket introduced by Ohsawa et al. solved the difficult problem of data transactions due to the particular characteristic of data, i.e. the safeguarding privacy. In order to make sure the mechanism of the market of data, there are some researchers proposed a gamified...
Different from current researches on Flickr group recommendation approaches that recommend groups to either users or images, this work proposes a unified framework that recommends groups to both users and images. Four types of entities in the Flickr system (users, tags, images, and groups) are integrated into a tetradic model, and then we uses tetradic decomposition to discover the latent semantic...
Representational state transfer (REST) is the current design standard for Web Application Programmable Interfaces (Web APIs or APIs). Unfortunately, existing Web API search engines allow for only keyword or tag-based searches for RESTful services without considering advanced functionality, such as contextual recommendation or visualization. In this paper, we propose a novel approach, referred to as...
Hashing methods have proven to be useful for a variety of tasks and have attracted extensive attention in recent years. Various hashing approaches have been proposed to capture similarities between textual, visual, and cross-media information. However, most of the existing works use a bag-of-words methods to represent textual information. Since words with different forms may have similar meaning,...
With the development of data science, the market of data also plays a significant role in the data mining domain gradually. This paper focus on how to use a visualization method based on contour map to seek the relationship between Data Jackets in order to create an innovative chance for data transaction. The analysis of results by questionnaires can illustrate the feasibility of this visualization...
Effect of adaptive threshold on shot boundary detection performance is analyzed in this paper, where the threshold is used to determine whether a target frame is a shot boundary or not in a broadcasting video content. Adaptive threshold is calculated using input threshold and visual similarities of adjacent frames of a target frame. The experimental results show that application of adaptive threshold...
Blocks-based programming environments offer an alternative program representation to textual source code that simplifies the considerations of syntax for novices. This position paper raises the question of whether additional affordances related to transparency of data, transparency of semantics, and liveness of execution can be consistently added to these environments to obtain some significant advantages...
In modern social media, massive visual and textual data are collected and uploaded to social websites everyday. How to extract useful knowledge from such multiple modality data and organize it in an efficient way remains an important problem. The goal of this dissertation is to investigate joint visual and textual mining for social media data. My dissertation aims at contributing to our theoretical...
This paper establishes the theoretical relation between the scores assigned by observers on continuous and discrete (q unevenly distributed classes) scales. The experimental results validate this theoretical relation and bring to light the impact of the semantic labels, generally associated to the quality levels, in the evaluation process. They consider image quality, depth perception and visual comfort...
Probabilistic Latent Semantic Analysis(PLSA) is the one of the main methods for texture analysis and computer vision. In practice, PLSA will result in overfitting problems, including the circumstance of unclear membership of topics and the case of high similarity between different topics. In this paper, we describe a dynamic threshold model based PLSA(dPLSA). It can make the ambiguous topic information...
The overwhelming proliferation of digital images on media sharing webs have triggered the requirement of effective tools to retrieve images of interest using semantic concepts. Due to the semantic gap between low-level visual features and high-level semantic concepts of an image, however, the performances of many existing automatic image annotation algorithms are not so satisfactory. In this paper,...
With the growing relevance of human interaction with infocommunications in general and augmented/virtual environments in particular, it is becoming increasingly important to provide users with a “virtual physics” capable of emulating the richness and subtle informativeness of multimodal feedback in the physical world. In this paper, we describe an extension to an existing immersive virtual sketching...
The aim of this paper was to develop an image browsing system, where only visual information is available for users and computers as well. Large image set is structured in albums and the idea was to select the most representative image from each album in the level of hierarchy, and then the next upper level in the hierarchy consists of these representative images. Selection of the most representative...
Bag-of-visual phrase (BoP) has been proposed and developed for landmark recognition recently. However, existing BoP methods for landmark recognition have two major shortcomings: (i) they try to construct a universal phrase vocabulary for all object categories, which lacks specific descriptive capabilities for a particular category, and (ii) they often adopt simple criterion such as the frequency information...
Nowadays tag-based image search on image retrieval systems like Flickr, Google does not provide the option of relevance-based ranking. In this paper, a relevance-based ranking scheme which integrates both the visual features and the semantic annotations is proposed. The semantic correlation between database images and input tags is described using an improved form of Google distance, and the visual...
Web-scale image understanding is a challenging but significant task to comprehend image contents on the internet. The de-facto standard methods based on machine learning or computer vision still suffer from a phenomenon of visual pol-ysemia and concept polymorphism (VPCP). To resolve the VPCP, Vicept has been proposed to characterize the membership distribution between visual appearances and semantic...
In this work the contribution of automatically-extracted (thus, imperfect) video structural semantics towards improving interactive video retrieval is examined. First, the automatic extraction of video structural semantics, i.e. the decomposition of the video into scenes that correspond to the different sub-stories or high-level events, is performed. Then, these are introduced to the interactive video...
A key problem in image annotation is to learn the underlying semantics. However, finding such semantic embeddings is a challenge task and often requires large amount of tagging information. In this paper, we propose to utilize multi-modality cues by incorporating visual and textual information as embedded objects. The paper further presents a multi-task learning framework that simultaneously learns...
Given the observation that content transformations tend to preserve semantic information, we demonstrated in previous research that model-free semantic concept detection can be successfully leveraged for identifying NDVCs. In this paper, we seek a better understanding of the usefulness of model-free semantic concept detection for both the task of annotation and NDVC detection. In particular, through...
Since the beginning of mankind, there has been a need to display knowledge in such a way that it could be easily understood. In today's highly technological world we face an overwhelming amount of information from a variety of sources, namely: business applications such as customer comments and communications, trade publications, internal research reports and competitor web sites. Most of this knowledge...
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