This paper introduces a maximum entropy method to Discourse Coherence Modeling (DCM). Different from the state-of-art supervised entity-grid model and unsupervised cohesion-driven model, the model we proposed only takes as input lexicon features, which increases the training speed and decoding speed significantly. We conduct an evaluation on two publicly available benchmark data sets via senten...

Previous work on text coherence was primarily based on matching multiple mentions of the same entity in different parts of the text; therefore, it misses the contribution from semantically related but not necessarily coreferential entities (e.g., Gates and Microsoft). In this paper, we capture such semantic relatedness by leveraging world knowledge (e.g., Gates is the person who created Microso...

Entity Linking (EL) has received considerable attention in recent years. Given many name mentions in a document, the goal of EL is to predict their referent entities in a knowledge base. Traditionally, there have been two distinct directions of EL research: one focusing on the effects of mention’s context compatibility, assuming that “the referent entity of a mention is reflected by its context...

One of the objectives of Forest Dragon 2 project is the generation of a forest cover change map between 1990s and 2000s for Northeast China based on ERS-1/2 tandem data and ENVISAT ASAR data. For the 1990s’ map, an automatic and seasonal-adaptive retrieval of forest biomass method was used to produce a forest biomass map based on the ERS tandem interferometric coherence. The biomass map was int...

The complex nature of organizational culture challenges our ability to infer its underlying dynamics from observational studies. Recent computational studies have adopted a distinctly different view, where plausible mechanisms are proposed to describe a wide range of social phenomena, including the onset and evolution of organizational culture. In this spirit, this work introduces an empiricall...

Question answering is different from information retrieval in that it attempts to answer questions by providing summaries from numerous retrieved documents rather than by simply providing a list of documents that requires users to do additional work. However, the quality of answers that question answering provides has not been investigated extensively, and the practical approach to presenting q...

Entity linking refers to the task of mapping name strings in a text to their corresponding entities in a given knowledge base. It is an essential component in natural language understanding applications, but a challenging task. This paper proposes a method that combines heuristics and learning for entity linking by (i) learning coherence among co-occurrence entities within the text based on Wik...

Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental respect: in EL the textual mention can be linked to a named entity which may or may not contain the exact mention, while in WSD there is a perfect match between the word form (better, its lemma) and a suitable word sense...