---
res:
  bibo_abstract:
  - Cyber-physical systems (CPS) and the Internet-of-Things (IoT) result in a tremendous
    amount of generated, measured and recorded time-series data. Extracting temporal
    segments that encode patterns with useful information out of these huge amounts
    of data is an extremely difficult problem. We propose shape expressions as a declarative
    formalism for specifying, querying and extracting sophisticated temporal patterns
    from possibly noisy data. Shape expressions are regular expressions with arbitrary
    (linear, exponential, sinusoidal, etc.) shapes with parameters as atomic predicates
    and additional constraints on these parameters. We equip shape expressions with
    a novel noisy semantics that combines regular expression matching semantics with
    statistical regression. We characterize essential properties of the formalism
    and propose an efficient approximate shape expression matching procedure. We demonstrate
    the wide applicability of this technique on two case studies. @eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Dejan
      foaf_name: Ničković, Dejan
      foaf_surname: Ničković
  - foaf_Person:
      foaf_givenName: Xin
      foaf_name: Qin, Xin
      foaf_surname: Qin
  - foaf_Person:
      foaf_givenName: Thomas
      foaf_name: Ferrere, Thomas
      foaf_surname: Ferrere
      foaf_workInfoHomepage: http://www.librecat.org/personId=40960E6E-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0001-5199-3143
  - foaf_Person:
      foaf_givenName: Cristinel
      foaf_name: Mateis, Cristinel
      foaf_surname: Mateis
  - foaf_Person:
      foaf_givenName: Jyotirmoy
      foaf_name: Deshmukh, Jyotirmoy
      foaf_surname: Deshmukh
  bibo_doi: 10.1007/978-3-030-32079-9_17
  bibo_volume: 11757
  dct_date: 2019^xs_gYear
  dct_identifier:
  - UT:000570006300017
  dct_isPartOf:
  - http://id.crossref.org/issn/0302-9743
  - http://id.crossref.org/issn/9783030320782
  dct_language: eng
  dct_publisher: Springer Nature@
  dct_title: Shape expressions for specifying and extracting signal features@
...