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Fine-grained sentiment analysis of online product reviews is important to both potential consumers and sellers. Automatically extracting appraisal expressions from online reviews is one of the key issues in fine-grained sentiment analysis. The existing ...

Address standardization is the process of recognizing and normalizing free-form addresses into a common standard format. In today's digital economy, this process is increasingly challenging such as in ecommerce fulfillment, logistic planning, ...

Keyphrases associated with research papers provide an effective way to find useful information in the large and growing scholarly digital collections. However, keyphrases are not always provided with the papers, but they need to be extracted from their ...

This paper addresses the problem of extracting and segmenting references from PDF documents. The novelty of the presented approach lies in its capability to discover highly varying references mainly in terms of content, length and location in the ...

Character-level sequence label tagging is the most efficient way to solve unknown words problem for Chinese word segment. But the most widely used model, Conditional Random Fields (CRF), needs a large amount of manual design features. So it is ...

As robots become increasingly prevalent in human environments, there will inevitably be times when the robot needs to interrupt a human to initiate an interaction. Our work introduces the first interruptibility-aware mobile-robot system, which uses ...

We propose a concurrent Fully Convolutional Networks(CFCN) structure which contains three Fully Convolutional Networks(FCN). Gaussian filter, Mean filter and Median filter are chosen to pre-process the original multimodal MR images. Then, we fuse the ...

Robots are increasingly being deployed in unstructured human environments where they will need to approach and interrupt collocated humans. Most prior work on robot interruptions has focused on how to interrupt a person or on estimating a human's ...

A large number of patients discuss treatments in online health communities (OHCs). One research question of interest to health researchers is whether treatments being discussed in OHCs are eventually used by community members in their real lives. In ...

Address Cleansing is a very challenging problem, in particular, for geographies where there is a lot of variability in address nomenclature. This paper explains how a machine learning classifier is used to build a model that not only identifies a valid ...

There are many studies that show using class-based features improves the performance of natural language processing (NLP) tasks such as syntactic part-of-speech tagging, dependency parsing, sentiment analysis, and slot filling in natural language ...

We develop an unsupervised learning framework for extracting popular product attributes from product description pages originated from different E-commerce Web sites. Unlike existing information extraction methods that do not consider the popularity of ...

Complex chronic diseases (e.g., autism, lupus, and Parkinson's) are remarkably heterogeneous across individuals. This heterogeneity makes treatment difficult for caregivers because they cannot accurately predict the way in which the disease will progress ...

Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common cause in adults with treatment-resistant epilepsy. Surgical resection of the lesion is the most effective treatment to stop seizures. Technical ...

This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine ...

In this paper, we present results of joint segmentation and classification of sequences in the framework of conditional random field (CRF) models. We use a recently proposed dual-functionality CRF model: on the first level, the proposed model conducts ...

Activity Recognition is an integral component of ubiquitous computing. Recognizing an activity is a challenging task since activities can be concurrent, interleaved or ambiguous and can consist of multiple actors (which would require parallel activity ...

We address the tasks of recovering bibliographic and document structure metadata from scholarly documents. We leverage higher order semi-Markov conditional random fields to model long-distance label sequences, improving upon the performance of the ...

We present several interrelated technical and empirical contributions to the problem of emotion-based music recommendation and show how they can be applied in a possible usage scenario. The contributions are (1) a new three-dimensional resonance-arousal-...

We present a new approach for predicting program properties from massive codebases (aka "Big Code"). Our approach first learns a probabilistic model from existing data and then uses this model to predict properties of new, unseen programs.

The key idea ...