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Methods for Mining and Summarizing Text Conversations (Synthesis Lecture on Data Management)

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Before the invention of the Internet and the creation of the Web, the vast majority of human conversations were in spoken form, with the only notable, but extremely limited, exception being epistolary exchanges. Some important spoken conversations, such as criminal trials and political debates (e.g., Hansard, the transcripts of parliamentary debates), have been transcribed for centuries, but the rest of what humans have been saying to each other, throughout their history, to solve problems, make decisions and more generally to interact socially, has been lost.

This situation has dramatically changed in the last two decades. At an accelerating pace, people are having conversations by writing in a growing number of social media, including emails, blogs, chats and texting on mobile phones. At the same time, the recent, rapid progress in speech recognition technology is enabling the development of computer systems that can automatically transcribe any spoken conversation.

The net result of this ongoing revolution is that an ever-increasing portion of human conver- sations can be stored as text in computer memory and processed by applying Natural Language Pro- cessing (NLP) techniques (originally developed for written monologues - e.g., newspapers, books). This ability opens up a large space of extremely useful applications, in which critical information can be mined from conversations, and summaries of those conversations can be effectively generated. This is true for both organizations and individuals. For instance, managers can find the information exchanged in conversations within a company to be extremely valuable for decision auditing. If a decision turns out to be ill-advised, mining and summarizing the relevant conversations may help in determining responsibility and accountability*. Similarly, conversations that led to favorable decisions could be mined and summarized to identify effective communication patterns and sources within the company. On a more personal level, an informative summary of a conversation could play at least two critical roles. On the one hand, the summary could greatly support a new participant to get up to speed and join an already existing, possibly long, conversation (e.g., blog comments). On the other hand, a summary could help someone to quickly prepare for a follow-up discussion of a conversation she was already part of, but which occurred too long ago for her to remember the details. Furthermore, the ability to summarize conversations will also be crucial in our increasingly mobile world, as a long incoming message or an extensive ongoing conversations could be much more easily inspected on a small screen in a concise, summarized form.

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