III: Small: Collaborative Research: RUI: Learning to Model Sequences

这个合作研究项目涉及康奈尔大学（IIS-1217686）和伊萨卡学院（IIS-1217485）的教师和学生在一个跨学科项目。学习序列预测模型的能力是几个应用问题的组成部分，从机器翻译的语言模型到推荐阅读材料以掌握某个主题。该项目的目标是开发新的机器学习算法，可以学习难以用属性描述的项目的序列模型。特别是，该项目开发的模型可以自动嵌入基于训练序列的潜在特征空间中的项目，可以集成部分和嘈杂的边信息，并具有建模长期依赖性的能力。由此产生的预测模型有可能被应用于科学和教育，并可以支持经济向在线商业应用的转变。该项目的重点是推荐音乐播放列表作为主要的测试平台。部署的在线音乐推荐系统不仅提供了测试和评估的框架，这个应用领域有助于吸引来自合作机构，康奈尔大学和伊萨卡学院（本科院校）的广泛学生，使本科生能够融入研究。项目成果，包括开放源码软件和附加说明的数据集，通过项目网址（http：//www.cs.cornell.edu/People/tj/playlists/）传播。

This collaborative research project involves faculty and students from Cornell University (IIS-1217686) and Ithaca College (IIS-1217485) in an interdisciplinary project. The ability to learn predictive models of sequences is a component in several application problems, ranging from language models for machine translation to the recommendation of material to read in order to master a subject. The goal of this project is to develop new machine learning algorithms that can learn sequence models for items that are difficult to describe by attributes. In particular, the project develops models that automatically embed items in a latent feature space based on training sequences, that can integrate partial and noisy side information, and that have the ability to model long-range dependencies.The resulting predictive models have a potential to be employed in science and education and can support the economic shift towards online business applications. The project focuses on the recommendation of music playlists as the main testbed. A deployed online music recommendation system not only provides the framework for testing and evaluation, this application domain helps to attract a broad spectrum of students from collaborating institutions, Cornell University and Ithaca College (an undergraduate institution), enabling the integration of undergraduates in the research. Project results, including open source software and annotated data set, are disseminated via the project Web site (http://www.cs.cornell.edu/People/tj/playlists/).