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Geographic information retrieval: Modeling uncertainty of user's context

机译：地理信息检索：用户上下文不确定性建模

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Geographic information retrieval (GIR) is nowadays a hot research issue that involves the management of uncertainty and imprecision and the modeling of user preferences and context. Indexing the geographic content of documents implies dealing with the ambiguity, synonymy and homonymy of geographic names in texts. On the other side, the evaluation of queries specifying both content based conditions and spatial conditions on documents' contents requires representing the vagueness and context dependency of spatial conditions and the personal user's preferences. The spatial condition can be specified linguistically in the query through vague terms such as "close to the North East of Milan", whose semantic depends on the user's context and perception of distance. Further, users may want to express queries in which the content condition and the spatial condition have a distinct preference and are combined with a distinct semantics. In this paper, we propose a geographic information retrieval model and a system implementing it that represents both the uncertainty in indexing the geographic documents' content and the user's context and preferences in evaluating flexible spatial queries. It extracts the geographic content from documents' text by applying heuristic knowledge coded by bipolar rules which evaluate positive hints and negative hints for the recognition of geographic names in text. Thus, it represents the geographic content of documents by fuzzy footprints, i.e., distinct locations on the earth associated with the text with a distinct degree of significance. Finally, the system allows evaluating two types of queries flexibly combining the content based condition with the spatial condition. The spatial condition is interpreted as the soft constraint "close" on the user's perceived distance between the documents' footprint and query's footprint. For each retrieved document, two relevance scores are computed with respect to the two query conditions that are flexibly combined to generate an overall ranked list of documents. The user can choose the semantic for the combination that can be either an asymmetric "and possibly" aggregation between the mandatory content condition and the optional spatial condition, or a compensative "average" aggregation, defined as a linear combination of the two conditions; further, a relative preference between the conditions can be specified to achieve personalization and effectiveness. A prototypal geographic information retrieval system, named Geo-Finder, based on this model is described, and its evaluations are discussed.
机译：如今，地理信息检索（GIR）是一个热门研究问题，涉及不确定性和不精确性的管理以及用户偏好和上下文的建模。对文档的地理内容建立索引意味着要处理文本中地理名称的歧义，同义和同音异义。另一方面，对在文档内容上指定基于内容的条件和空间条件的查询的评估需要表示空间条件和个人用户的偏好的模糊性和上下文相关性。可以在查询中通过诸如“靠近米兰东北”的模糊术语在语言上指定空间条件，其语义取决于用户的上下文和对距离的感知。此外，用户可能希望表达这样的查询，其中内容条件和空间条件具有不同的偏好并且与不同的语义相结合。在本文中，我们提出了一种地理信息检索模型和一个实现该模型的系统，该模型既代表了对地理文档内容建立索引的不确定性，又代表了评估灵活空间查询时用户的上下文和偏好。它通过应用由双极规则编码的启发式知识从文档的文本中提取地理内容，该启发式知识对正面提示和负面提示进行评估，以识别文本中的地理名称。因此，它通过模糊的足迹来表示文档的地理内容，即与文本相关联的地球上具有显着程度的不同位置。最终，系统允许评估两种类型的查询，以灵活地将基于内容的条件与空间条件相结合。空间条件被解释为对用户在文档覆盖范围和查询覆盖范围之间的感知距离的“约束”软约束。对于每个检索到的文档，针对两个查询条件计算两个相关性分数，这两个查询条件可以灵活组合以生成文档的总体排名列表。用户可以为组合选择语义，该语义可以是强制性内容条件和可选空间条件之间的不对称“可能”聚合，也可以是定义为两个条件的线性组合的补偿性“平均”聚合；此外，可以指定条件之间的相对偏好以实现个性化和有效性。描述了基于该模型的原型地理信息检索系统Geo-Finder，并讨论了其评估。

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