Global Entity Ranking Across Multiple Languages

Collaborative Ranking: A Case Study on Entity Linking

In this paper, we present a new ranking scheme, collaborative ranking (CR). In contrast to traditional non-collaborative ranking scheme which solely relies on the strengths of isolated queries and one stand-alone ranking algorithm, the new scheme integrates the strengths from multiple collaborators of a query and the strengths from multiple ranking algorithms. We elaborate three specific forms ...

A Dea- Compromise Programming Model for Comprehensive Ranking

This paper addresses comprehensive ranking systems determining an ordering of entities by aggregating quantitative data for multiple attributes. We propose a DEA-CP (Data Envelopment Analysis Compromise Programming) model for the comprehensive ranking, including preference voting (ranked voting) to rank candidates in terms of aggregate vote by rank for each candidate. Although the DEA-CP model ...

Multilingual Multimodal Language Processing Using Neural Networks

We live in an increasingly multilingual multimodal world where it is common to find multiple views of the same entity across modalities and languages. For example, news articles which get published in multiple languages are essentially different views of the same entity. Similarly, video, audio and multilingual subtitles are multiple views of the same movie clip. Given the proliferation of such...

Metacognitive (Rending) Strategies Across Languages and Techniques

Automatically Extracting Personal Name Aliases from the Web

An entity can be referred by multiple name aliases on the web. Extracting aliases of an entity is important for various tasks such as identification of relations among entities, automatic metadata extraction and entity disambiguation. To extract relations among entities properly, one must first identify those entities. Aliases of an entity are useful as metadata for that entity and can be used ...