4 accepted papers
We propose a practical instant question answering (QA) system on product pages of e-commerce services, where for each user query, relevant community question answer (CQA) pairs are retrieved. User queries and CQA pairs differ significantly in language characteristics making relevance learning diffic…
In this paper, we present LATEX-Numeric - a high-precision fully-automated scalable framework for extracting E-commerce numeric attributes from unstructured product text like product description. Most of the past work on attribute extraction is not scalable as they rely on manually curated training…
In this work, we address the problem of cross-modal retrieval in presence of multi-label annotations. In particular, we introduce multi-label Canonical Correlation Analysis (ml-CCA), an extension of CCA, for learning shared subspaces taking into account high level semantic information in the form o…
With the help of a convolutional neural network~(CNN) trained to recognize objects, a scene image is represented as a bag of semantics (BoS). This involves classifying image patches using the network and considering the class posterior probability vectors as locally extracted semantic descriptors. T…