Contextual advertising using keyword extraction through collocation

Khan, Suleman; Ilyas, Qazi Mudassar; Anwar, Waqas

doi:10.1145/1838002.1838081

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…Dhiman et al [29] used GLCM and LBP for content-based image retrieval to apply to the CORAL dataset. Suleman et al [30] and Zeeshan et al [31] used contextual techniques to find similarities in 1D and 2D signals. Sukhjeet et al [32] used a hybrid approach which utilizes color space and quaternion moment vector to create this unique feature vector.…”

Section: State Of the Artmentioning

confidence: 99%

PCA-Based Advanced Local Octa-Directional Pattern (ALODP-PCA): A Texture Feature Descriptor for Image Retrieval

et al. 2022

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This paper presents a novel feature descriptor termed principal component analysis (PCA)-based Advanced Local Octa-Directional Pattern (ALODP-PCA) for content-based image retrieval. The conventional approaches compare each pixel of an image with certain neighboring pixels providing discrete image information. The descriptor proposed in this work utilizes the local intensity of pixels in all eight directions of its neighborhood. The local octa-directional pattern results in two patterns, i.e., magnitude and directional, and each is quantized into a 40-bin histogram. A joint histogram is created by concatenating directional and magnitude histograms. To measure similarities between images, the Manhattan distance is used. Moreover, to maintain the computational cost, PCA is applied, which reduces the dimensionality. The proposed methodology is tested on a subset of a Multi-PIE face dataset. The dataset contains almost 800,000 images of over 300 people. These images carries different poses and have a wide range of facial expressions. Results were compared with state-of-the-art local patterns, namely, the local tri-directional pattern (LTriDP), local tetra directional pattern (LTetDP), and local ternary pattern (LTP). The results of the proposed model supersede the work of previously defined work in terms of precision, accuracy, and recall.

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Section: State Of the Artmentioning

confidence: 99%

PCA-Based Advanced Local Octa-Directional Pattern (ALODP-PCA): A Texture Feature Descriptor for Image Retrieval

et al. 2022

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“…The different nature and disorderly structures require an exceptionally extended data source on the World Wide Web to give solace to the clients. However, these devices are not sufficiently grown to allow coordinated information designs and records ending up being a profoundly compelling variable for the exploration engineers to advance more shrewd devices for information extraction and to spread its data set to give an undeniable degree of authoritative incentive on the web (Khan et al, 2009). This would require the creation of an intricate and complex AI framework equipped for self-ruling action to find and structure web information (Xu et al, 2011).…”

Section: Web Miningmentioning

confidence: 99%

Transformative Effects of Big Data on Advanced Data Analytics: Open Issues and Critical Challenges

Kumari¹,

Muthulakshmi²

2022

Journal of Computer Science

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We are living in the period of the information era (i.e., where data/information is the new oil for companies/industries). The term big data had been authored to depict this age. This study characterizes a lot on the idea of big data and its progress over the previous decade to till date. This study presents the meaning of this new idea and its qualities and additionally examines a few different things identified with few interesting issues. In big data, it is found that vulnerability can be taken care of physically or consequently (distinguishing proof or potentially separation of irregularities). Around 7 V's of big data, speed, gazetteers, and information bases should be persistently refreshed and information handled can be occasionally (at the standard time). It is found that in an event it is required to handle assortment, manage different information designs (tweets and regular language messages), and circulated information. To handle/tackle issues in sectors like medical science, agriculture, business, online trade, transportation, etc., big data role is essential. Smart things which are producing big data (through their communications) require analysis of this data for making effective solutions to such real-time applications. Hence, this study discusses work done towards big data concerning its current status, challenges to security and privacy, and future directions. In the last, this study may lead future researchers to a different potential of applications and research.

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“…To solve the three-horned dilemma of either low-relevance or high-latency or high-load in contextual advertising, Anagnostopoulos et al [1] used text summarization techniques paired with external knowledge to craft short page summaries in real time. Khan et al [15] proposed a strategy which is based on collocation between different words to find out an optimal match between an advertisement and web page. Fan et al [8] presented a SOCA (Sentiment-Oriented Contextual Advertising) framework that aims to combine contextual advertising matching with sentiment analysis to select advertisements that are related to the positive and neutral aspects of a blog and rank them according to their relevance.…”

Section: Related Workmentioning

confidence: 99%