8828427
Detecting geographic locations from web resources
The rapid pervasion of the web into users' daily lives has put much importance on capturing location-specific information on the web, due to the fact that most human activities occur locally around where a user is located. This is especially true in the increasingly popular mobile and local search environments. Thus, how to correctly and effectively detect geographic locations from web resources has become a key challenge to location-based web applications. In our previous work, we proposed to explicitly distinguish three types of locations for web resources, namely provider location, content location and serving location. Provider location is the physical location of the provider who owns the web resource; content location is the geographic location described in the web content; while serving location is the geographic scope that a web resource can reach. In this paper, we present a system that comprehensively employs a set of algorithms and different geographic sources by extracting geographic information from the web content, and mining hyperlink structures as well as user logs. As the result, only relevant geographic sources, rather than all of possible ones are used in computation of each category of web location. Finally, experimental results on large samples of web data show that our solution outperforms previous approaches.
6641983
An adaptive web page layout structure for small devices
The limited display size of current small Internet devices is becoming a serious obstacle to information access. In this paper, we introduce a Document REpresentation for Scalable Structures (DRESS) to help information providers make composite documents, typically web pages, scalable in both logic and layout structure to support effective information acquisition in heterogeneous environments. Through this novel document representation structure based on binary slicing trees, the document can dynamically adapt its presentation according to display sizes by maximizing the information throughput to users. We discuss the details of this structure with its key attributes. An automatic approach for generating this structure for existing web pages is also presented. A branch-and-bound algorithm and a capacity ratio-based slicing method are proposed to select proper content representation and aesthetic document layouts respectively. A set of user study experiments have been carried out and the results show that compared with the thumbnail-based approach, the DRESS-based interface can reduce browsing time by 23.5%.
18031163
Browsing large pictures under limited display sizes
Pictures have become increasingly common and popular in mobile communications. However, due to the limitation of mobile devices, there is a need to develop new technologies to facilitate the browsing of large pictures on the small screen. In this paper, we propose a set of novel approaches which are able to aid or automate common image browsing tasks on mobile devices. All of these approaches are based on an image attention model which is employed to illustrate the information structure within an image. An efficient algorithm to generate the optimal browsing path based on the information foraging theory is presented. Experimental evaluations of the proposed mechanism indicate that our approach is an effective way for viewing large images on small displays
37379077
Improving Web Browsing on Small Devices Based on Table Classification
Browsing large web pages on small screens is still very inconvenient due to their limited display sizes. A straightforward solution is eliminating the annoying horizontal scrolling requirement, i.e. present all the contents into a single narrow column, usually named one-column view. It is implemented by deleting the layout that will cause horizontal scrolling. However, after deleting the layout structure, some structural information becomes unreadable, like data tables. In this paper, we propose an approach to improve web browsing on small devices by classifying HTML tables into data tables and layout tables. For data tables, we try to preserve the original structural information in the final presentation. Therefore, the browsing experience can be improved for the one-column view. Experimental results show that our approach can achieve a satisfactory performance.
10740927
Photo-to-search: using multimodal queries to search the web from mobile devices
Nowadays, mobile phones with the digital camera are getting more and more popular. With necessary technologies, they are possible to become a powerful tool to search the Web on the go. Most Web search engines only support text queries. Therefore, users have to convert their information needs into words. However, it is sometimes difficult to describe the needs in text and the text input is inconvenient on small devices. To solve the problem, we propose a system named Photo-to-Search which allows users to input multimodal queries. Particularly, we study queries with captured images and optional text messages in this paper. For example, the user can simply take a photo of the flower and input a few terms like "flower". Textually relevant Web images are retrieved according to the query terms. Afterwards, the snapped picture is compared with these images by the CBIR (Content Based Image Retrieval) method. According to the context of the visually similar images, related key phrases are extracted. Finally, the search results are returned in multiple forms. Our system can also search for very similar images on the Web, such as movie posters or photos of film stars, to find related information. Experimental results on the large scale data showed our system achieved satisfactory efficiency and performance.
12125361
Hybrid index structures for location-based web search
There is more and more commercial and research interest in location-based web search, i.e. finding web content whose topic is related to a particular place or region. In this type of search, location information should be indexed as well as text information. However, the index of conventional text search engine is set-oriented, while location information is two-dimensional and in Euclidean space. This brings new research problems on how to efficiently represent the location attributes of web pages and how to combine two types of indexes. In this paper, we propose to use a hybrid index structure, which integrates inverted files and R*-trees, to handle both textual and location aware queries. Three different combining schemes are studied: (1) inverted file and R*-tree double index, (2) first inverted file then R*-tree, (3) first R*-tree then inverted file. To validate the performance of proposed index structures, we design and implement a complete location-based web search engine which mainly consists of four parts: (1) an extractor which detects geographical scopes of web pages and represents geographical scopes as multiple MBRs based on geographical coordinates; (2) an indexer which builds hybrid index structures to integrate text and location information; (3) a ranker which ranks results by geographical relevance as well as non-geographical relevance; (4) an interface which is friendly for users to input location-based search queries and to obtain geographical and textual relevant results. Experiments on large real-world web dataset show that both the second and the third structures are superior in query time and the second is slightly better than the third. Additionally, indexes based on R*-trees are proven to be more efficient than indexes based on grid structures.
27158603
A simulation-based optimization method for production-distribution network design
Production-distribution network design is a critical decision that has significant impacts on a supply chain's long-term performance. Supply chain dynamics, such as demand fluctuation, and transportation instability, are omitted in most mathematical models due to tractability. We present a simulation-based optimization method in this paper for multi-criteria production-distribution network design. The method consists of a multiobjective optimizer and a simulation module. The optimizer, based on a multiobjective genetic algorithm, is used to direct the search for compromised solutions regarding to various criteria. Candidate solutions are evaluated by the discrete-event simulation module, developed in a flexible manner that enables automatic simulation of various supply chain structures without human intervention. The method is applied to a case study from automotive industry. A set of Pareto-optimal solutions are obtained, including decisions on the open/close decisions on facilities, order splitting ratios and inventory control policies.
1014578
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks
Gradient-following learning methods can encounter problems of implementation in many applications, and stochastic variants are sometimes used to overcome these difficulties. We analyze three online training methods used with a linear perceptron: direct gradient descent, node perturbation, and weight perturbation. Learning speed is defined as the rate of exponential decay in the learning curves. When the scalar parameter that controls the size of weight updates is chosen to maximize learning speed, node perturbation is slower than direct gradient descent by a factor equal to the number of output units; weight perturbation is slower still by an additional factor equal to the number of input units. Parallel perturbation allows faster learning than sequential perturbation, by a factor that does not depend on network size. We also characterize how uncertainty in quantities used in the stochastic updates affects the learning curves. This study suggests that in practice, weight perturbation may be slow for large networks, and node perturbation can have performance comparable to that of direct gradient descent when there are few output units. However, these statements depend on the specifics of the learning problem, such as the input distribution and the target function, and are not universally applicable.
10241359
Localising surface defects in random colour textures using multiscale texem analysis in image eigenchannels
A novel method is presented to detect defects in random colour textures which requires only a very few normal samples for unsupervised training. We decorrelate the colour image by generating three eigenchannels in each of which the surface texture image is divided into overlapping patches of various sizes. Then, a mixture model and EM is applied to reduce groupings of patches to a small number of textural exemplars, or texems. Localised defect detection is achieved by comparing the learned texems to patches in the unseen image eigenchannels.
6927574
A Charged Active Contour Based on Electrostatics
We propose a novel active contour model by incorporating particle based electrostatic interactions into the geometric active contour framework. The proposed active contour, embedded in level sets, propagates under the joint influence of a boundary attraction force and a boundary competition force. Unlike other contour models, the proposed vector field dynamically adapts by updating itself when a contour reaches a boundary. The model is then more invariant to initialisation and possesses better convergence abilities. Analytical and comparative results are presented on synthetic and real images.
12048322
Inspecting Colour Tonality on Textured Surfaces
We present a multidimensional histogram method to inspect tonality on colour textured surfaces, e.g. ceramic tiles. Comparison in the noise dominated chromatic channels is error prone. We perform vector- ordered colour smoothing and generate a PCA-based reconstruction of a query tile based on a reference tile eigenspace. Histograms of local feature vectors are then compared for tonality defect detection. The proposed method is compared and evaluated on a data set with groundtruth.