Financial Narrative Summarisation Using a Hybrid TF-IDF and Clustering Summariser: AO-Lancs System at FNS 2022

Computing and Communications

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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Financial Narrative Summarisation Using a Hybrid TF-IDF and Clustering Summariser: AO-Lancs System at FNS 2022. / El-Haj, Mahmoud; Ogden, Andrew.
2022. 88-91 Paper presented at The 4th Financial Narrative Processing Workshop, Marseille, France.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Bibtex

@conference{e63fb0098cdc4f5aa9595523b5e5181b,

title = "Financial Narrative Summarisation Using a Hybrid TF-IDF and Clustering Summariser: AO-Lancs System at FNS 2022",

abstract = "This paper describes the HTAC system submitted to the Financial Narrative Summarization Shared Task (FNS-2022). A methodology implementing Financial narrative Processing (FNP) to summarise financial annual reports, named Hybrid TF-IDF and Clustering (HTAC). This involves a hybrid approach combining TF-IDF sentence ranking as an NLP tool with a state-of-the-art Clustering Machine learning model to produce short 1000-word summaries of long financial annual reports. These Annual Reports are a legal responsibility of public companies and are in excess of 50,000 words. The model extracts the crucial information from these documents, discarding the extraneous content, leaving only the crucial information in a shorter, non-redundant summary. Producing summaries that are more effective than summaries produced by two pre-existing generic summarisers.",

author = "Mahmoud El-Haj and Andrew Ogden",

year = "2022",

month = jun,

day = "15",

language = "English",

pages = "88--91",

note = "The 4th Financial Narrative Processing Workshop, FNP 2022 ; Conference date: 24-06-2022 Through 24-06-2022",

url = "http://wp.lancs.ac.uk/cfie/fnp2022/",

}

RIS

TY - CONF

T1 - Financial Narrative Summarisation Using a Hybrid TF-IDF and Clustering Summariser: AO-Lancs System at FNS 2022

AU - El-Haj, Mahmoud

AU - Ogden, Andrew

N1 - Conference code: 4

PY - 2022/6/15

Y1 - 2022/6/15

N2 - This paper describes the HTAC system submitted to the Financial Narrative Summarization Shared Task (FNS-2022). A methodology implementing Financial narrative Processing (FNP) to summarise financial annual reports, named Hybrid TF-IDF and Clustering (HTAC). This involves a hybrid approach combining TF-IDF sentence ranking as an NLP tool with a state-of-the-art Clustering Machine learning model to produce short 1000-word summaries of long financial annual reports. These Annual Reports are a legal responsibility of public companies and are in excess of 50,000 words. The model extracts the crucial information from these documents, discarding the extraneous content, leaving only the crucial information in a shorter, non-redundant summary. Producing summaries that are more effective than summaries produced by two pre-existing generic summarisers.

AB - This paper describes the HTAC system submitted to the Financial Narrative Summarization Shared Task (FNS-2022). A methodology implementing Financial narrative Processing (FNP) to summarise financial annual reports, named Hybrid TF-IDF and Clustering (HTAC). This involves a hybrid approach combining TF-IDF sentence ranking as an NLP tool with a state-of-the-art Clustering Machine learning model to produce short 1000-word summaries of long financial annual reports. These Annual Reports are a legal responsibility of public companies and are in excess of 50,000 words. The model extracts the crucial information from these documents, discarding the extraneous content, leaving only the crucial information in a shorter, non-redundant summary. Producing summaries that are more effective than summaries produced by two pre-existing generic summarisers.

UR - https://aclanthology.org/2022.fnp-1.12

M3 - Conference paper

SP - 88

EP - 91

T2 - The 4th Financial Narrative Processing Workshop

Y2 - 24 June 2022 through 24 June 2022

ER -

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