A new approach to unsupervised text summarization

Nomoto, Tadashi; Matsumoto, Yūji

doi:10.1145/383952.383956

Cited by 103 publications

(58 citation statements)

References 11 publications

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“…The research presents various natural language processing (NLP) techniques for mining and summarizing text conversations. Nomoto and Matsumoto [6] also present a novel approach that exploits the diversity of concepts in text. A diversity-based approach is a principled generalization of the Maximal…”

Section: Literature Reviewmentioning

confidence: 99%

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You’ve Got Email: A Workflow Management Extraction System

Chaipornkaew

Prexawanprasut

McAleer

2017

J. Rev. Global Econ.

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Email is one of the most powerful tools for communication. Many businesses use email as the main channel for communication, so it is possible that substantial data are included in email content. In order to help businesses grow faster, a workflow management system may be required. The data gathered from email content might be a robust source for a workflow management system. This research proposes an email extraction system to extract data from any incoming emails into suitable database fields. The database, which is created by the program, has been planned for the implementation of a workflow management system. The research is presented in three phases: (1) define suitable criteria to extract data; (2) implement a program to extract data, and store them in a database; and (3) implement a program for validating data in a database. Four criteria are applied for an email extraction system. The first criterion is to select contact information at the end of the email content; the second criterion is to select specified keywords, such as tel, email, and mobile; the third criterion is to select unique names, which start with a capital letter, such as the names of people, places, and corporates; the fourth criterion is to select special texts, such as Co. Ltd, .com, and www. The empirical results suggest that when all four criteria are considered, the accuracy of a program and percentage of blank fields are at an acceptable level compared with the results from other criteria. When four criteria are applied to extract 7,340 emails in English, the accuracy of this experiment is approximately 68.66%, while the percentage of blank fields in a database is approximately 68.05. The database created by the experiment can be applied in a workflow management system. KeywordsBusiness operations, startup business, import/export industry, email, business data, workflow management system, business transactions, migrating, email extraction system. Revised: May 2017 * The authors would like to express their gratitude to the Executive Vice-President of Finish International Freight Co. Ltd, as well as another two anonymous companies which cannot be mentioned because of confidentiality. The companies provided very useful information and insights to conduct this research. Thanks also to Khun Natthicha Phonjan and Khun Sariporn Plipon, who assisted greatly to edit and verify the accuracy of the program. It is appreciated that the business data provided by the three selected businesses are sensitive, and will not be disclosed or used for any purpose other than the research for the paper. The authors are also grateful for the helpful comments and suggestions of Chia-Lin Chang. Corresponding author: Takorn Prexawanprasut (takorn.pre@dpu.ac.th) 1 JEL Classification AbstractEmail is one of the most powerful tools for communication. Many businesses use email as the main channel for communication, so it is possible that substantial data are included in email content. In order to help businesses grow faster, a workflow management system ma...

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Section: Literature Reviewmentioning

confidence: 99%

“…In addition to a diversity-based approach in Nomoto and Matsumoto [6], the researchers also apply an information-centric approach where the quality of summaries is judged not in terms of how well they match human-created summaries but in terms of how well they represent their source documents in text categorization.…”

Section: Literature Reviewmentioning

confidence: 99%

You’ve Got Email: A Workflow Management Extraction System

Chaipornkaew

Prexawanprasut

McAleer

2017

J. Rev. Global Econ.

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“…keyphrases and key sentences, is relevant to our problem. There are two types of extraction, i.e., supervised [2], [6], [7], [9] and unsupervised methods [1], [3], [4], [8], [10], [11]. Natural language processing techniques [12], [13], [14] have also been used for keyphrase extraction.…”

Section: Related Workmentioning

confidence: 99%

Bidirectional Extraction of Phrases for Expanding Queries in Academic Paper Retrieval

Win¹,

Masada²

2016

ijarai

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Abstract-This paper proposes a new method for query expansion based on bidirectional extraction of phrases as word n-grams from research paper titles. The proposed method aims to extract information relevant to users' needs and interests and thus to provide a useful system for technical paper retrieval. The outcome of proposed method are the trigrams as phrases that can be used for query expansion. First, word trigrams are extracted from research paper titles. Second, a co-occurrence graph of the extracted trigrams is constructed. To construct the co-occurrence graph, the direction of edges is considered in two ways: forward and reverse. In the forward and reverse co-occurrence graphs, the trigrams point to other trigrams appearing after and before them in a paper title, respectively. Third, Jaccard similarity is computed between trigrams as the weight of the graph edge. Fourth, the weighted version of PageRank is applied. Consequently, the following two types of phrases can be obtained as the trigrams associated with the higher PageRank scores. The trigrams of the one type, which are obtained from the forward co-occurrence graph, can form a more specific query when users add a technical word or words before them. Those of the other type, obtained from the reverse co-occurrence graph, can form a more specific query when users add a technical word or words after them. The extraction of phrases is evaluated as additional features in the paper title classification task using SVM. The experimental results show that the classification accuracy is improved than the accuracy achieved when the standard TF-IDF text features are only used. Moreover, the trigrams extracted by the proposed method can be utilized to expand query words in research paper retrieval.

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“…A modified K-means algorithm using the Minimum Description Length Principle (MDL) is used, where the number of clusters are estimated, which otherwise has to be supplied by the user [20]. Using K-means, the diversity in the document is obtained in the form of clusters.…”

Section: G K-means Clustering Followed By Tfidfmentioning

confidence: 99%

A Survey of Unstructured Text Summarization Techniques

Elfayoumy¹,

Thoppil²

2014

IJACSA

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Abstract-Due to the explosive amounts of text data being created and organizations increased desire to leverage their data corpora, especially with the availability of Big Data platforms, there is not usually enough time to read and understand each document and make decisions based on document contents. Hence, there is a great demand for summarizing text documents to provide a representative substitute for the original documents. By improving summarizing techniques, precision of document retrieval through search queries against summarized documents is expected to improve in comparison to querying against the full spectrum of original documents.Several generic text summarization algorithms have been developed, each with its own advantages and disadvantages. For example, some algorithms are particularly good for summarizing short documents but not for long ones. Others perform well in identifying and summarizing single-topic documents but their precision degrades sharply with multi-topic documents. In this article we present a survey of the literature in text summarization. We also surveyed some of the most common evaluation methods for the quality of automated text summarization techniques. Last, we identified some of the challenging problems that are still open, in particular the need for a universal approach that yields good results for mixed types of documents.

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A new approach to unsupervised text summarization

Cited by 103 publications

References 11 publications

You’ve Got Email: A Workflow Management Extraction System

You’ve Got Email: A Workflow Management Extraction System

Bidirectional Extraction of Phrases for Expanding Queries in Academic Paper Retrieval

A Survey of Unstructured Text Summarization Techniques

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