AI SearchContrastive learning with template{u2019}s prompt in multiple aspect dialogue summarization (Record no. 22947)
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| 005 - DATE AND TIME OF LATEST TRANSACTION | |
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| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12421820 |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.DSAI-23-11 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Worachot Nakduk |
| 245 10 - TITLE STATEMENT | |
| Title | Contrastive learning with template{u2019}s prompt in multiple aspect dialogue summarization |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 39 leaves : |
| Other physical details | ill. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. DSAI-23-11 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence, School of Engineering and Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Eng.) - Asian Institute of Technology, 2023 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Dialogue summarizing compresses the essential information from a conversation into a concise paragraph, enabling individuals to efficiently understand the main ideas without needing to look into the surrounding context. Recently, pre-trained language models have the potential to be helpful for dialogue summaries. Due to the engagement of sev eral participants, topic deviations, frequent references to previous statements, diverse interaction messages, and specific vocabulary, these variables contribute to increased complexity for summarizers. It can generate misinformation and generate misleading content that only covers partial facts of a conversation. Furthermore, a single discourse has the ability to incorporate multiple topics without a clearly defined boundary between them. The realistic importance of the dialogue summarization model can be better char acterized by assessing numerous aspects, such as the speaker{u2019}s goal or the specific topic under discussion. However, current summarization systems produce generic summaries that lack personalization and fail to align with customer preferences and expectations. To address this limitation, create customized different aspects of the produced summaries by engaging with the summarization process through textual submission in a format of descriptive prompts. In this paper, we present Contrastive Learning with a Topic Length Template Prompt for Dialogue Summarization. We select a topic either from the goal summary or attractive topics. These topics serve as a control signal, guided by a template{u2019}s prompt. We utilize contrastive learning methods to enhance the diversity of prompts in the template by using synonym replacement and random topics. These methods enable us to generate both positive and negative topics, thereby increasing the quantity of meaningful information available for training. Additionally, we use special tokens to highlight words and prompts to focus on important keywords. Experimentally, we show that our model can increase the ROUGE score in the DialogSum testing dataset. Our models are available at https://github.com/worachot-n/topic-length.git |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Natural language processing (Computer science) |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chaklam Silpasuwanchai, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mongkol Ekpanyapong, |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dailey, Matthew N., |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | His Majesty the King{u2019}s Scholarships (Thailand), |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. DSAI-23-11 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B20439">http://203.159.5.9/ait-thesis/detail.php?q=B20439</a> |
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| CREATED | CREATED : 2024-02-29 |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Price effective from | Koha item type | Barcode | Copy number |
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| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.DSAI-23-11 | 18/08/2026 | 18/08/2026 | 67-Electronic Resource | ||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.DSAI-23-11 | 18/08/2026 | 18/08/2026 | 40-Archives | 30050120898811 | 1 |