Nitin Jain

Nitin Jain

Noida, Uttar Pradesh, India
1K followers 500+ connections

About

I own vision, strategy and execution at high growth E-Commerce and FinTech unicorns. Some…

Activity

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Experience

  • Tokopedia Graphic
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    Indonesia

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    Noida Area, India

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    Gurgaon, India

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    Noida Area, India

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    Noida Area, India

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    Noida Area, India

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    Noida Area, India

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    Bangalore, India

Education

Publications

  • Automatic Layout Element Detection From E-Commerce Pages

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    We present a novel framework of automatically detecting layout elements from e-commerce product pages. A layout element is typically defined as a html element that corresponds to a unique SKU (Stock Keeping Unit) selection option on a given product page. Automated extraction of such elements allows for efficient and richer structuring of e-commerce catalog. Existing methods address this problem from a page segmentation perspective. Hence, such methods are unable to detect specific elements that…

    We present a novel framework of automatically detecting layout elements from e-commerce product pages. A layout element is typically defined as a html element that corresponds to a unique SKU (Stock Keeping Unit) selection option on a given product page. Automated extraction of such elements allows for efficient and richer structuring of e-commerce catalog. Existing methods address this problem from a page segmentation perspective. Hence, such methods are unable to detect specific elements that allow automatic selection of a particular SKU. In this paper, we propose a relatively unsupervised and fully automated approach to solving this problem. First, we describe a cascaded feature extraction pipeline which is both computationally efficient as well as robust to presence of large number of noisy irrelevant html elements present in product pages. Second, an Outlier Detection based scheme is outlined that ingests the robust features from previous phase and builds an efficient model of ”regular” or non-layout html elements. This model is then applied on a test page to detect any ”outlier” which corresponds to a layout element. Preliminary experiments conducted on 4 different merchants illustrate the superior performance of our proposed method.

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Languages

  • English

    Native or bilingual proficiency

  • Hindi

    Native or bilingual proficiency

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