Let me break down the L33t (http://en.wikipedia.org/wiki/Leet) for you for you and take the time to officially thank you. Especially, I would like to thank all of the n00bs out there that make my job easy. You know who you are; all those n00bs using your computers without taking the time or understand how to [...]
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Posted 03 July 2010
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270 INC
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In this series of articles, you will be exposed to the dark side of the Internet. Through interviews, independent research and real-world examples, you will experience the dangers of the World Wide Web.Travel with me down the “rabbit hole” as we explore the dark side of the Internet. Let me set the stage. Before sharing [...]
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Posted 03 July 2010
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270 INC
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Researchers have employed a variety of methods to improve their chatbot’s accuracy. Most current chatbots use a dialog management module and knowledge base and rules, which they use with templates to match user input. Improving chatbot accuracy may be accomplished through expanding the chatbot knowledge base, improving upon the standard rule-based conversation method for chatbots, [...]
Some researchers are designing chatbots with the intent of integrating more natural human-like interactions (De Angeli & Brahnam, 2008). Specifically, the developer may program certain responses that would sacrifice accuracy, but confer more human-like traits (Sing et al., 2006). For example, if a chatbot is presented with a math problem it could wait, as if [...]
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Posted 11 April 2009
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Research
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Tagged: ALICE, artificial intelligence, Chatbot, data mining, human-like characteristics, Human-Like Qualities of Chatbots, human-like traits, mixed-initiative, natural language processing, on-line risk management tool, researcher, Risk Manager, statistical natural language processing methods, utterance
The major goal of building a better chatbot is to improve its interactions with humans. A wide variety of techniques including developing different architectures, incorporating quirks or tricks, or using different machine learning approaches have been used to improve either chatbot accuracy or human-like qualities. First, some ways that researchers are trying to improve human-like [...]
Since chatbots have moved into the public realm, there has been interest in evaluating how users interact with chatbots. For example, after analyzing conversations with the chatbot jabberwacky, one study found that the topics and style of conversations were broad (De Angeli & Brahnam, 2008). Users displayed different attitudes ranging from nice to nasty and [...]
The majority of current chatbots use a rule-based approach to interact with the user. In order to imitate human conversations, developers use a linguistic model combined with computational algorithms to build chatbots. Depending on the chatbot, rules can be based on simple textual pattern matching or complicated rules based on inference mechanisms (De Angeli & [...]
Chatbots need to effectively process natural language. Since starting around the 1960′s, natural language processing (NLP) research has had slow progress until the 1990′s (Lester, Branting, & Mott, 2004). NLP research has been greatly enhanced by development of large corpora of tagged text, as well as by development of better statistical machine learning and other [...]
The goal of a chatbot is to simulate the human use of language which brings up several questions. How do humans use language between themselves in similar settings? How can computers be made to understand natural language? How does the chatbot know what to reply to a user’s input? (Saygin et al., 2000). In overall [...]