In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

[Q]: The rise of smart applications has drawn interest to logical reasoning over data streams. Recently, different query languages and stream processing/reasoning engines were proposed in different communities. However, due to a lack of theoretical foundations, the expressivity and semantics of these diverse approaches are given only informally. Towards clear specifications and means for analytic study, a formal framework is needed to define their semantics in precise terms. To this end, we present a first step towards an ideal semantics that allows for exact descriptions and comparisons of stream reasoning systems.
[A]: Towards Ideal Semantics for Analyzing Stream Reasoning


[Q]: An RDF data shape is a description of the expected contents of an RDF document (aka graph) or dataset. A major part of this description is the set of constraints that the document or dataset is required to satisfy. W3C recently (2014) chartered the RDF Data Shapes Working Group to define SHACL, a standard RDF data shape language. We refer to the ability to name and reference shape language elements as recursion. This article provides a precise definition of the meaning of recursion as used in Resource Shape 2.0. The definition of recursion presented in this article is largely independent of language-specific details. We speculate that it also applies to ShEx and to all three of the current proposals for SHACL. In particular, recursion is not permitted in the SHACL-SPARQL proposal, but we conjecture that recursion could be added by using the definition proposed here as a top-level control structure.
[A]: Recursion in RDF Data Shape Languages


[Q]: The human intelligence lies in the algorithm, the nature of algorithms lies in the classification, and the classification is equal to outlier detection. This paper is based on its past unpublished edition (2009), which discussed an application of פ (pe) algorithm in outlier detection for time series data. The פ algorithm, also named as RDD algorithm, is originated from the study on general AI. United with it, designed modules can be used to realize kinds of tasks. A primary framework concerned with the mind through פ algorithm has been constructed in prior works. In this concise paper, we neglect background and minor description of the early edition, and directly discuss the main contents include longest k–turn subsequence problem, curve type outliers, futural directions and related comments. In section “Past Present”, we keep all prior conclusions, though a little might be out of date.
[A]:
פ Algorithm: its past present, futue present and comments