Supporting Exploratory Search via the Semantic Web

我的工作主要关注的是如何通过有效地展示如何探索信息以及如何表示可以探索的资源的汇合，来改善在正确的时间访问Web上正确的信息。我的目标是找到一种方法，让任何人都能更容易地从他们所知道的开始，并能够利用这些知识来帮助他们探索信息，建立他们想要的知识。例如，其中一个挑战是帮助一个对古典音乐一无所知的人找到他们可能喜欢的古典音乐。为了迎接这个挑战，我们创造了一个新的界面范例，将音频线索与丰富的上下文中的信息联系起来，这样人们就可以使用他们所知道的——不管他们是否喜欢他们所听到的——和他们想要的——能够探索这个领域，找到他们喜欢听到的片段。本文档的封面显示了该交互的屏幕截图，可以在beta.mspace.fm上试用。这项工作涉及前端需求和设计，分布式异构信息的信息体系结构。最近，这项工作主要关注语义网传递信息的潜力，通过基于机器的推理，语义网在信息点之间提供比当前Web更丰富的关联。信息不仅可以通过原始搜索结果进行探索，还可以通过多种上下文进行探索，从当前的工作情况到可能给予返回源的信任级别。例如，对在语义支持的Web上探索乳腺癌感兴趣的人将能够从多个属性（如病因、治疗方法、历史观点、当前研究、诊断实践等）探索这个概念。一个外行人在研究治疗方法时，可能会看到谁领导了一种特定的方法，也可能希望看到他们做了什么其他的工作，同样地，探索人们自己的治疗经历是什么。他们可能希望主要关注以非专业术语提出的这项工作的描述，但不一定将医学期刊排除在他们的观点之外。这里的第一个挑战是如何使这些相关信息的网络易于处理，以便以一种最尊重搜索本身上下文的方式进行探索：外行读者。与信息表示相关的是根据信任（语义网的一个关键组件）来表示这些信息。一些东西。因此，上述场景中的主要挑战是：呈现高度相关信息的复杂网络的一般策略，用于跨维度搜索的创新查询。策略/信任规模提议的跨三个站点的协作有三个相互建立的阶段。到目前为止，语义Web研究中的交互工作都是建立在已知知识库之上的，其中图是预先已知的，UI可以使用这些已知的约束。在MIT的DIG实验室中，我们将研究如何从这些方法中进行推广，以支持更多类似web的交互。也就是说，如何在没有预先构造的部分域表示的连接图之间进行探索。说明这个空间的一个挑战是，想象一个人如何在古典音乐的背景下看待贝多芬，在探索的同时，能够看到贝多芬和拿破仑之间的政治联系。麻省理工学院的工作重点将是考虑为这种有意义的探索表示大规模的网络规模的图形。在马里兰大学的思维实验室和HCIL实验室，我们将研究如何在这种探索中使政策/信任机制易于处理。仅仅为标准交互实践提出一个模型是不够的：评估它是至关重要的。这些Web上的新技术所提供的新型探索需要创新的评估方法：跨（语义）Web等丰富关联空间的任务可以移动

My work has largely been concerned with how to improve access to the right information at the right time on the Web via effective presentation both of how to explore information as well as how to represent the confluence of sources that can be explored. My goal is to find ways to make it ever easier for anyone to start with what they know and be able to use that to help them explore information to build the knowledge they want. For instance, one challenge was to help someone who knew nothing about Classical Music find Classical Music they might like. For this challenge, we created a new interface paradigm that connected audio cues with information in a rich context so that one could use what they did know - whether or not they liked what they heard - with what they wanted - being able to explore the domain to find pieces they would enjoy hearing. The cover of this document shows a screen shot of that interaction, and can be tried at beta.mspace.fm. The work involved both front end requirements and design, information architecture for distributed heterogeneous information Most recently this work has focused on the potential of the Semantic Web to deliver information that can, by machine-based inference, provide richer associations among points of information than the current Web. Information can be explored not only via raw search results but via multiple contexts, from current work situation to the level of trust one may give a returned source. For example, a person interested in exploring breast cancer on a semantically enabled Web will be able to explore this concept from multiple attributes, such as causes, treatments, historical perspectives, current research, diagnostic practices and so on. A lay person looking at treatments may see who has lead a particular approach, and may wish to see what other work they've carried out and, equally, explore what people's own experiences of the treatment have been. They may wish to look primarily at descriptions of this work presented in non-specialist terms, but not have medical journals necessarily excluded from their view. The first challenge here is how to make these networks of associated information tractable in order to be explorable and in a way that best respects the context of the search itself: a lay reader. Related to the representation of the information is presenting this information in terms of Trust, a key component of the Semantic Web. Something something. Key challenges in the above scenario therefore are:General strategies for presenting complex networks of highly associated informationInnovative queries for cross dimensional searches.Policy/Trust ScaleThe proposed collaboration across three sites has three phases which build upon each other. So far, interation efforts in Semantic Web research have been built on top of known knowledge bases, where the graph is known in advance and the UI can work with these known constraints. At MIT's DIG lab, we will look at how to generalize from these approaches to support more Web-like interaction. That is, how to explore across connected graphs where there is no pre-constructed representation of part of that domain. A challenge to illustrate this space is to imagine how a person looking at Beethoven within the context of Classical Music would be able to see paths, while exploring, that would lead to political connections between Beethoven and Napoleon. The focus of work at MIT will be to consider representing massive Web scale graphs for such meaningful exploration. At the University of Maryland's MindLab and HCIL lab, we will be looking at how policy/trust mechanisms can be made tractable within such explorations. It is not sufficient to propose a model for standard interaction practice: it is critical to evaluate it. The new types of exploration afforded by these new technologies on the Web call for innovative methods in evaluation: tasks across a richly associated space like the (Semantic) Web can move