相关论文: Toward the Evaluation of Written Proficiency on a …

Language identification is a critical component of language processing pipelines (Jauhiainen et al.,2019) and is not a solved problem in real-world settings. We present a lightweight and effective language identifier that is robust to…

In this study, we explore peer-interaction effects in online networks on speaking skill development. In particular, we present an evidence for gradual buildup of skills in a small-group setting that has not been reported in the literature.…

Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility…

Answering multiple-choice questions in a setting in which no supporting documents are explicitly provided continues to stand as a core problem in natural language processing. The contribution of this article is two-fold. First, it describes…

We introduce the problem of proficiency modeling: Given a user's posts on a social media platform, the task is to identify the subset of posts or topics for which the user has some level of proficiency. This enables the filtering and…

GRank is a recent graph-based recommendation approach the uses a novel heterogeneous information network to model users' priorities and analyze it to directly infer a recommendation list. Unfortunately, GRank neglects the semantics behind…

The task of expert finding has been getting increasing attention in information retrieval literature. However, the current state-of-the-art is still lacking in principled approaches for combining different sources of evidence in an optimal…

Some social networks, such as LinkedIn and ResearchGate, allow user endorsements for specific skills. In this way, for each skill we get a directed graph where the nodes correspond to users' profiles and the arcs represent endorsement…

Mining topical experts on social media is a problem that has gained significant attention due to its wide-ranging applications. Here we present the first study that combines data from four major social networks -- Twitter, Facebook, Google+…

Automated speaking assessment in conversation tests (ASAC) aims to evaluate the overall speaking proficiency of an L2 (second-language) speaker in a setting where an interlocutor interacts with one or more candidates. Although prior ASAC…

Social network websites, such as Facebook, YouTube, Lastfm etc, have become a popular platform for users to connect with each other and share content or opinions. They provide rich information for us to study the influence of user's social…

Deep neural networks have emerged as a powerful technique for learning representations from user-item interaction data in collaborative filtering (CF) for recommender systems. However, many existing methods heavily rely on unique user and…

This paper presents a description and evaluation of the ROC Speak system, a platform that allows ubiquitous access to communication skills training. ROC Speak (available at rocspeak.com) enables anyone to go to a website, record a video,…

In this paper I propose a new way of measuring linguistic productivity that objectively assesses the ability of an affix to be used to coin new complex words and, unlike other popular measures, is not directly dependent upon token…

Data sparsity, that is a common problem in neighbor-based collaborative filtering domain, usually complicates the process of item recommendation. This problem is more serious in collaborative ranking domain, in which calculating the users…

Statistical methods have been widely employed in recent years to grasp many language properties. The application of such techniques have allowed an improvement of several linguistic applications, which encompasses machine translation,…

Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques. Furthermore, this information can be used in offline processes of root cause analysis.…

This study was motivated by the problem of identifying fake documents on the Internet. To explore possible solutions to this problem we introduce a model of a network community in which members submit documents with verifiable content.…

In the Internet era the information overload and the challenge to detect quality content has raised the issue of how to rank both resources and users in online communities. In this paper we develop a general ranking method that can…

Considering the large amount of content created online by the minute, slang-aware automatic tools are critically needed to promote social good, and assist policymakers and moderators in restricting the spread of offensive language, abuse,…