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| Content Provider | ACM Digital Library |
|---|---|
| Author | Ade-Ibijola, Abejide |
| Abstract | Instant messaging (IM) has gained huge popularity, not only in the social space, but in many sectors of work and everyday life. One such sector is finance, where IMs are used for bargaining, trading and many other financial information exchanges between parties. A popular IM software in finance is the Instant Bloomberg (IB). The conversations (chat histories) recorded via IB often contain crucial information about the financial positions of the market, quotes for different instruments, as well as unimportant texts. Automatic comprehension of this type of text is a natural language processing task. In this paper we employ front-end compiler analyses in the automatic comprehension and summarisation of financial chats retrieved from IB. Taking the result, we present a software tool called FINCHAN that takes lengthy chat histories and attempts to recognise the syntax up to a success rate of 98%, extracts semantic information to 61% success rate, generates concise summaries of these chats, and offers analyses of hidden patterns, text-to-speech synthesis of generated summaries, with functionalities for archiving/indexing IMs. |
| Starting Page | 1 |
| Ending Page | 10 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450348058 |
| DOI | 10.1145/2987491.2987518 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-09-26 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Financial instant messages Context-free grammar Summarisation Instant bloomberg Comprehension |
| Content Type | Text |
| Resource Type | Article |
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