III: Small: Models and Measures for Novel and Diverse Search Results

传统的信息检索模型假定文档是独立相关的。然而，用户通常希望看到检索到的文档涵盖几个子主题，或不同的可能解释，或查询的相关信息。在这些情况下，将文档建模为独立相关并不能提供最佳用户体验。本研究项目试图通过文件相互依赖的新模型和新的评估措施来弥补这一点。这项工作有三个主线：(1)实现排序算法所需的多样性、新颖性和冗余性模型；(2)文档排序中多样性、新颖性和冗余性的度量；(3)针对这些度量优化模型结构和参数。本项目涉及的主要挑战包括：如何对不同任务和领域的搜索结果之间的相关性和相互依赖性进行建模；如何预测多样性程度；以及如何评估新模型。新模型包括基于集合的检索模型和基于模式的检索模型，新的度量包括基于集合的标注、基于列表的偏好等。模型将使用现有的度量和新的度量进行评估，并将通过深入的统计分析对新的度量进行评估。该项目的结果包括一套模型和措施，将新颖性和多样性与不同领域的相关性结合起来，包括生物医学搜索、法律搜索和网络搜索。该项目的深远潜在影响是全面提高搜索引擎的利用率。该项目涉及生物医学搜索、法律或专利搜索以及网络搜索的具体应用，反映了搜索引擎在其中很重要的主要领域，在这些领域，改进的新颖性和多样性模型将直接改善用户体验。项目成果，包括出版物和评价数据集，将通过项目网站(http://ir.cis.udel.edu/monads).

Traditional models of information retrieval assume documents are independently relevant. However, users often want to see the retrieved documents cover several subtopics, or different possible interpretations, or nuggets of relevant information for a query. In these cases, modeling documents as independently relevant does not provide the optimal user experience. This research project attempts to remedy this with new models of document interdependence and new evaluation measures. There are three threads running through this work: (1) the models of diversity, novelty, and redundancy that will be needed to implement ranking algorithms; (2) measurements of diversity, novelty, and redundancy in a ranking of documents; and (3) optimizing model structures and parameters to the measures.The main challenges addressed in this project include: how to model relevance along with interdependencies among search results for different tasks and domains; how to predict the degree of diversity; and how to evaluate the new models. The new models include set-based and pattern-based retrieval models, and the new measures include set-based labeling, list-based preference etc. The models will be evaluated with the existing measures as well as the new measures, and the new measures will be evaluated with in-depth statistical analysis. The result of this project includes a suite of models and measures that combine novelty and diversity with relevance for different domains, including biomedical search, legal search and Web search.The far-reaching potential impact of this project is an improvement in search engine utility across the board. The project addresses specific applications to biomedical search, legal or patent search, and web search reflect major domains in which search engines are important and in which improved models for novelty and diversity would directly improve the user experience. Project results, including publications and evaluation datasets, will be disseminated via the project website (http://ir.cis.udel.edu/monads).