Papers Re-Ranking

Addressing Community Question Answering in English and Arabic

This paper studies the impact of different types of features applied to learning to re-rank questions in community Question Answering. We tested our models on two datasets released in SemEval-2016 Task 3 on "Community Qu…

Three Tiers Neighborhood Graph and Multi-graph Fusion Ranking for Multi-feature Image Retrieval: A Manifold Aspect

Single feature is inefficient to describe content of an image, which is a shortcoming in traditional image retrieval task. We know that one image can be described by different features. Multi-feature fusion ranking can b…

Labeling Topics with Images using Neural Networks

Topics generated by topic models are usually represented by lists of $t$ terms or alternatively using short phrases and images. The current state-of-the-art work on labeling topics using images selects images by re-ranki…

Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration

Candidate re-ranking for SMT-based grammatical error correction

Large-Scale Location Recognition and the Geometric Burstiness Problem

Visual location recognition is the task of determining the place depicted in a query image from a given database of geo-tagged images. Location recognition is often cast as an image retrieval problem and recent research …

Re-ranking Object Proposals for Object Detection in Automatic Driving

Object detection often suffers from a plenty of bootless proposals, selecting high quality proposals remains a great challenge. In this paper, we propose a semantic, class-specific approach to re-rank object proposals, w…

On Improving Informativity and Grammaticality for Multi-Sentence Compression

Multi Sentence Compression (MSC) is of great value to many real world applications, such as guided microblog summarization, opinion summarization and newswire summarization. Recently, word graph-based approaches have bee…

GIFT: A Real-time and Scalable 3D Shape Search Engine

Projective analysis is an important solution for 3D shape retrieval, since human visual perceptions of 3D shapes rely on various 2D observations from different view points. Although multiple informative and discriminativ…

2-Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search

The method of random projections has become a standard tool for machine learning, data mining, and search with massive data at Web scale. The effective use of random projections requires efficient coding schemes for quan…

Mutual Information and Diverse Decoding Improve Neural Machine Translation

Sequence-to-sequence neural translation models learn semantic and syntactic relations between sentence pairs by optimizing the likelihood of the target given the source, i.e., $p(y|x)$, an objective that ignores other po…

A Contextual Language Model to Improve Machine Translation of Pronouns by Re-ranking Translation Hypotheses

plWordNet in Word Sense Disambiguation task

The paper explores the application of plWordNet, a very large wordnet of Polish, in weakly supervised Word Sense Disambiguation (WSD). Because plWordNet provides only partial descriptions by glosses and usage examples, a…

Improving Human Activity Recognition Through Ranking and Re-ranking

We propose two well-motivated ranking-based methods to enhance the performance of current state-of-the-art human activity recognition systems. First, as an improvement over the classic power normalization method, we prop…

VRFP: On-the-fly Video Retrieval using Web Images and Fast Fisher Vector Products

VRFP is a real-time video retrieval framework based on short text input queries, which obtains weakly labeled training images from the web after the query is known. The retrieved web images representing the query and eac…

Particular object retrieval with integral max-pooling of CNN activations

Recently, image representation built upon Convolutional Neural Network (CNN) has been shown to provide effective descriptors for image search, outperforming pre-CNN features as short-vector representations. Yet such mode…

G-Bean: an ontology-graph based web tool for biomedical literature retrieval

Currently, most people use PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to …

Dependency-Based Semantic Role Labeling using Convolutional Neural Networks

Query by String word spotting based on character bi-gram indexing

In this paper we propose a segmentation-free query by string word spotting method. Both the documents and query strings are encoded using a recently proposed word representa- tion that projects images and strings into a …

A Re-ranking Model for Dependency Parser with Recursive Convolutional Neural Network

In this work, we address the problem to model all the nodes (words or phrases) in a dependency tree with the dense representations. We propose a recursive convolutional neural network (RCNN) architecture to capture synta…