@inproceedings{,
    author = {Ullrich, Sabine; Geierhos, Michaela},
    title = {Towards Constructing Multi-hop Reasoning Chains using Local Cohesion},
    editor = {},
    booktitle = {The CODE 2021 Annual Conference (2021, München)},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2021},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {https://www.unibw.de/code-events/05_ullrich.pdf},
    doi = {},
    keywords = {},
    abstract = {For complex questions in question-answering systems, simple information extraction techniques are not sufficient to provide a satisfactory answer. To explain why an answer is correct and to provide a cohesive line of argumentation, reasoning chains can be useful. For more challenging questions, multi-hop reasoning chains help to connect consecutive sentences. Currently, however, multi-hop reasoning can only be detected when key entities overlap between two connected sentences. To address this problem, we will study the linguistic features of highly cohesive argumentation chains in order to apply them in more general models. Local cohesion is defined by the connectedness of sequences at the sentence level. While this measure is currently mainly used for automated essay scoring, we propose to use local cohesion to detect connections between sentences when none or not all crucial words overlap. Instead, cohesive lexical and structural features such as synonyms, paraphrases, and hypernyms should be considered. After analyzing multi-hop reasoning chains, new delexicalized chain representations are abstracted to construct generalized reasoning chains.},
    note = {},
    institution = {Universität der Bundeswehr München, Fakultät für Informatik, INF 7 - Institut für Datensicherheit, Professur: Geierhos, Michaela},
    
    
}