Мақалалар

In November 2014, the European Cen- tral Bank (ECB) started to directly su- pervise the largest banks in the Euro- zone via the Single Supervisory Mecha- nism (SSM). While supervisory risk as- sessments are usually based on quantita- tive data and surveys, this work explores whether sentiment analysis is capable …...

We propose an image-mediated learning approach for cross-lingual document re- trieval where no or only a few parallel corpora are available. Using the images in image-text documents of each language as the hub, we derive a common seman- tic subspace bridging two languages by means of generalized canonical correla- tion …...

The difficult language in Electronic Health Records (EHRs) presents a challenge to patients’ understanding of their own con- ditions. One approach to lowering the barrier is to provide tailored patient ed- ucation based on their own EHR notes. We are developing a system to retrieve EHR note-tailored online consumer ori- …...

Community question answering, a recent evolution of question answering in the Web context, allows a user to quickly con- sult the opinion of a number of people on a particular topic, thus taking advantage of the wisdom of the crowd. Here we try to help the user by deciding automat- …...

Open domain targeted sentiment is the joint information extraction task that finds target mentions together with the senti- ment towards each mention from a text corpus. The task is typically modeled as a sequence labeling problem, and solved us- ing state-of-the-art labelers such as CRF. We empirically study the effect …...

This paper studies Cumulative Citation Recommendation (CCR) - given an entity in Knowledge Bases, how to effectively detect its potential citations from volume text streams. Most previous approaches treated all kinds of features indifferently to build a global relevance model, in which the prior knowledge embedded in docu- ments cannot …...

This paper presents a framework to model the semantic representation of binary re- lations produced by open information ex- traction systems. For each binary relation, we infer a set of preferred types on the two arguments simultaneously, and gen- erate a ranked list of type pairs which we call schemas. …...

We consider the task of named entity recognition for Chinese social media. The long line of work in Chinese NER has fo- cused on formal domains, and NER for social media has been largely restricted to English. We present a new corpus of Weibo messages annotated for both name and …...

Temporal taggers are usually developed for a certain language. Besides English, only few languages have been addressed, and only the temporal tagger HeidelTime covers several languages. While this tool was manually extended to these lan- guages, there have been earlier approaches for automatic extensions to a single tar- get language. …...

The enormous amount of information on the Internet has raised the challenge of highlight- ing new information in the context of already viewed content. This type of intelligent inter- face can save users time and prevent frustra- tion. Our goal is to scale up novelty detec- tion to large web …...

Syntactic features play an essential role in identifying relationship in a sentence. Pre- vious neural network models directly work on raw word sequences or constituent parse trees, thus often suffer from irrele- vant information introduced when subjects and objects are in a long distance. In this paper, we propose to …...

Automatic construction of knowledge graphs (KGs) from unstructured text has received considerable attention in recent research, resulting in the con- struction of several KGs with millions of entities (nodes) and facts (edges) among them. Unfortunately, such KGs tend to be severely sparse in terms of number of facts known for …...

Because of polysemy, distant labeling for information extraction leads to noisy train- ing data. We describe a procedure for re- ducing this noise by using label propaga- tion on a graph in which the nodes are entity mentions, and mentions are cou- pled when they occur in coordinate list structures. …...

Scientific theories and models in Earth sci- ence typically involve changing variables and their complex interactions, including correlations, causal relations and chains of positive/negative feedback loops. Vari- ables tend to be complex rather than atomic entities and expressed as noun phrases containing multiple modifiers, e.g. oxygen depletion in the upper …...

Semi-supervised bootstrapping techniques for relationship extraction from text iter- atively expand a set of initial seed rela- tionships while limiting the semantic drift. We research bootstrapping for relationship extraction using word embeddings to find similar relationships. Experimental results show that relying on word embeddings achieves a better performance on the …...

We present a novel fine-tuning algorithm in a deep hybrid architecture for semi- supervised text classification. During each increment of the online learning pro- cess, the fine-tuning algorithm serves as a top-down mechanism for pseudo-jointly modifying model parameters following a bottom-up generative learning pass. The resulting model, trained under what …...

Sponsored search is at the center of a multibil- lion dollar market established by search tech- nology. Accurate ad click prediction is a key component for this market to function since the pricing mechanism heavily relies on the estimation of click probabilities. Lexical fea- tures derived from the text of …...

We consider a novel setting for Named En- tity Recognition (NER) where we have ac- cess to document-specific knowledge base tags. These tags consist of a canonical name from a knowledge base (KB) and en- tity type, but are not aligned to the text. We explore how to use KB …...

We use character-based statistical machine translation in order to correct user search queries in the e-commerce domain. The training data is automatically extracted from event logs where users re-issue their search queries with potentially corrected spelling within the same session. We show results on a test set which was annotated …...

The prevalence of temporal references across all types of natural language utter- ances makes temporal analysis a key is- sue in Natural Language Processing. This work adresses three research questions: 1/is temporal expression recognition spe- cific to a particular domain? 2/if so, can we characterize domain specificity? and 3/how can …...