Chat bots
Mohit, Amit, Abhipreet,
Rohitashwa, Jimmie
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t is a GUI Desktop Based Project. As the title of the project i.e, “Omni-Bot” which implie, Schemes and Mind Maps of Computer Communication Systems
It is a GUI Desktop Based Project. As the title of the project i.e, “Omni-Bot” which implies its specification that, it is a guide which help us to solve our most of the problems ,this is a type of A.I Chat-Bot which acts just like a human from the Chat-Bot which acts just like a human from the outside.[7:47 pm, 31/10/2023] Sanjana: It the mean time Everything is data and data is everywhere ,most of the people having lots of issues to store and retrieve the data with specific Questions, in order to reduce the effort and Questions, in order to reduce the effort and provide a single based Answer to the question (chat–Bot) act as medium. It also provides a lots of Opportunities to young generation in Digital world as a developer. [7:48 pm, 31/10/2023] Sanjana: objective----------To solve the problem of the user and provide them the better results.Its advance GUI and user friendly. It works with and without the internet. It provides all the subjective output in short period of time.iiuy
Typology: Schemes and Mind Maps
2023/2024
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Chat bots
Mohit, Amit, Abhipreet,
Rohitashwa, Jimmie
What are chatbots?
• A chatbot is a conversational agent that
interacts with users using natural
language.
• Started as an attempt to fool humans.
• Numerous applications of chatbots such
as Customer Service, call centers etc
Need for chatbots?
- (^) You: Hello
- (^) Op: Hi. This is Railway Enquiry
- (^) You: What is the status of train 2803?
- (^) Op: It’s right on time. The train will leave CST at
5:45 pm. Is there anything else I could assist you
with?
- (^) You : No, thank you
- (^) Op: You are welcome. Indian railways wishes a nice
and happy journey.
History
• ELIZA
o (^) Developed in the 1960s o (^) Looks for pronouns and verbs o (^) ‘You’ becomes ‘I’ and vice versa o (^) User: You are a dork. o (^) ELIZA: What makes you think I am a dork?
• PARRY (1972)
o (^) Simulated a paranoid schizophrenic
Excerpt from the book
History (contd.)
- (^) ALICE o (^1994) o (^) Three time loebner prize winner o (^) Richard Wallace o (^) http://www.alicebot.org/
How Do Chatbots Work
- (^) Don’t have a good understanding of conversation
- (^) Are based on pattern matching
- (^) Chatterbots have a set of input and output rules
- (^) Recognize cue words from user and responds with a pre-calculated response
- (^) For e.g.:- Human: “I am feeling very worried today.” Chatterbot: “Why are you feeling worried lately?”
- (^) Other chatterbots learn through user interactions
ELIZA
- (^) One of the first chatterbots designed in 1966
- (^) Parodies a therapist rephrasing statements of the
user and posing them back as questions
- (^) Works by simple parsing and substitution of key
words into canned phrases
- (^) People get emotionally caught up by ELIZA’s
confident replies forgetting that it’s a machine
Jabberwacky
- (^) No fixed rules and principles programmed into it
- (^) Learns language and context through human interaction. Stores all conversations and comments which are used to find appropriate responses
- (^) Problems faced due to this approach:-
- (^) Continuous changing of subject and conversation
- (^) May respond in a bad-tempered and rude manner
- (^) Was designed to pass the Turing test and is the winner of the Loeber Prize contest
ALICE Chatbot System
- (^) ALICE(Artificial Linguistic Internet Computer
Entity) is inspired by ELIZA
- (^) Applies heuristic pattern matching rules to input
to converse with user
- (^) ALICE is composed of two parts
- (^) Chatbot engine
- (^) Language Model
- (^) Language models are stored in AIML(Artificial
Intelligence Mark-up Language) files
Types of ALICE/AIML Categories
- (^) Atomic categories: do not have wildcard symbols.
- (^) Default categories: have wildcard entries * or _.
Continued
- (^) Recursive categories: Symbolic Reduction: Divide and Conquer:
ALICE Pattern Matching Algorithm
- (^) Normalization is applied for each input, removing all punctuations, split in two or more sentences and converted to uppercase. E.g.: Do you, or will you eat me?. Converted to: DO YOU OR WILL YOU EAT ME
- (^) AIML interpreter then tries to match word by word the longest pattern match. We expect this to be the best one.
Algorithm
- (^) Assume the user input starts with word X.
- (^) Root of this tree structure is a folder of the file system that contains all patterns and templates.
- (^) The pattern matching uses depth first techniques. The folder has a subfolder stars with ,then, ”/”,scan through and match all words suffixed X, if no match then: Go back to the folder, find another subfolder start with word X, if so then turn to “X/”,scan for matching the tail of X. Patterns are matched. If no match then: Go back to the folder, find a subfolder starting with ,turn to, “/”, try all suffixes of input following “X” to see one match. If no match was found, change directory back to the parent of this folder and put “X” back to the head of the input.