Natural Language Processing - Artificial Intelligence I | CS 5314, Study Guides, Projects, Research of Computer Science

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TABLE OF CONTENTS

**1. DESCRIPTION OF THE PROJECT................................................................................................... 1

2. NATURAL LANGUAGE PROCESSING (NLP)................................................................................ 3** 2.1. MORPHOLOGICAL ANALYSIS:......................................................................................................... 3 2.2. SYNTACTIC ANALYSIS:..................................................................................................................... 3 2.3. SEMANTIC ANALYSIS:...................................................................................................................... 3 2.4. DISCOURSE INTEGRATION:.............................................................................................................. 3 **2.5. DISCOURSE AND PRAGMATIC PROCESSING................................................................................... 4
3. DEDUCTIVE REASONING SYSTEMS............................................................................................. 5
4. CONCLUSION....................................................................................................................................... 6
5. REFERENCES....................................................................................................................................... 7
6. DESCRIPTION OF THE PROJECT.....................................................................................................
7. NATURAL LANGUAGE PROCESSING (NLP)................................................................................ 3** 2.1. MORPHOLOGICAL ANALYSIS:......................................................................................................... 3 2.2. SYNTACTIC ANALYSIS:..................................................................................................................... 3 2.3. SEMANTIC ANALYSIS:...................................................................................................................... 3 2.4. DISCOURSE INTEGRATION:.............................................................................................................. 3 **2.5. DISCOURSE AND PRAGMATIC PROCESSING................................................................................... 4
8. DEDUCTIVE REASONING SYSTEMS............................................................................................. 5
9. Conclusion............................................................................................................................................... 6** Tutorial Team Second Date 12/6/2020 2:47 AM Page ii

“Talking” with Anna provides users with a comfortable level of interaction using a natural conversation style of communicating. She is a cheerful and patient animated drawing of a woman with a headset who blinks, smiles , makes gestures and even politely answers personal questions such as “who are you?” , “how are you?”, “where are you”, all in complete sentences. Anna relies on linguistic theory and a complex database to answer questions in natural language and when she doesn’t understand the query or is unable to answer it, she asks the users to direct their request to a human counterpart via e-mail. The problem with Anna is that she gives up extremely fast and frustrates users when she doesn’t meet her purpose of existence. Some of the agents mentioned here are developed using software applications such as Kiwilogic Lingubot, Graphico, and different Artificial Intelligence Markup Languages (AIML). The design and creation of these agents are based on using several artificial intelligence techniques dealing with natural language processing and deductive systems. These techniques are briefly discussed in the following sections of this tutorial. Tutorial Team Second Date Page

2. Natural Language Processing (NLP)

In more detail, processing written text which is a subtask of NLP is completed by using lexical, syntactic, and semantic knowledge of the language as well as any required real world information. The steps in the process of natural language understanding are:

2.1. Morphological analysis:

Words and special characters are analyzed and separated.

2.2. Syntactic analysis:

Parsing process which determines and structures the functions of words in an input sentence. Some constraints like word order are used in the process. Usually a derivation tree is ideal for representing those structures. These trees own syntactical rules which are used to recognize combined words that form sentences that are part of the language. These rules are called grammar..

2.3. Semantic analysis:

Once the structure is created, a meaning must be given to it. Individual words are mapped into objects in the knowledge base in order for the structure to now the wayhow the meaning of the individual words interactmeanings of the individual words interact with each other. Semantic Analysis After doing this, syntactic processing semantic analysis can use two different approaches: a) Lexical Processing: eEach word contained in the sentence being analyzed is searched in the dictionary. Since a word can have multiple meanings there are processes needed to choose the correct meaning within a context such as word sense disambiguation or lexical disambiguation.. b) Sentence-Level Processing: This process includes semantic grammars, case grammars, and conceptual dependencies in order to determine the meaning of a sentence.

2.4. Discourse integration:

Individual sentences are dependable to previous sentences and may influence those yet to come. The entities that structure those sentences may be related to entities that also were previous or may be introduced explicitly. The overall discourse must be coherent.. Tutorial Team Second Date Page

3. Deductive reasoning systems

Deductive reasoning refers to Aristotle logic. Inference is deductive reasoning in which the conclusion is of no greater generality than the premises. Is the inference in which the conclusion is just as certain as the premises, the conclusion of a deductive inference is necessitated by the premises: the premises can’t be true while the conclusion is false. Deductive reasoning systems use tools like Axiomatization. Axiomatization can be considered as sequence of statements such that every statement can be derived from those before it. The statement can be traduced into formal notation and the system can process and interpret them. Deductive reasoning systems provide a way to derive valid formulae without the need to inspect interpretations. Deductive systems use a general Framework. Thise method works by first by translating sentences in modal logic into constraint logic. The framework converts an ordinary first-order inference rules into inference rules for constraint logic. Additionally the relation between sets of inference rules for classical logic and inference rules for modal logic is made clear. Finally the special purpose-reasoner mechanism handles the constraints.. Tutorial Team Second Date Page

4. Conclusion

In order to create a virtual help system, the designer must pay special attention to different Artificial Intelligence techniques and be able to combine them. For a successful implementation, a knowledge base must be carefully created so that the knowledge-base agent uses its content and integrates it by processing the user’s queries accordingly. It is important to remember that the goal of creating a virtual assistant is to try to “humanize” the interaction between user and the technological system so it seems like a natural conversation is taking place. It is not advantageous to create an agent that - instead of providing help to the user - will become some sort of obstacle instead of a tool. Virtual assistant or help systems can make life easier for visitors on a web site by enabling them to quickly find exactly what they are looking for. They can also reduce the necessity for having a human entity answer all customer service calls. Help systems can provide an important role as part of the integrated e-commerce system by answering product questions as well as highlighting promotional opportunities. Tutorial Team Second Date Page