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NLIDB(Natural Language Interface to DataBases)

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NLIDB(Natural Language Interface to DataBases)

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NLIDB(Natural Language Interface to DataBases)

  1. 1. NATURAL LANGUAGE INTERFACE TO DATABASES P.Swetha
  2. 2. CONTENTS  What is NLIDB  Purpose of NLIDB  Architecture of NLIDB  Where NLIDB is used  Advantages  Disadvantages  Conclusion
  3. 3. WHAT IS NATURAL LANGUAGE INTERFACE TO DATABASES. The idea of using natural language instead of SQL has prompted the development of new type of processing method called Natural Language Interface to DataBase Systems (NLIDB). NLIDB is a step towards the development of Intelligent DataBase Systems (IDBS) to enhance the users in performing flexible querying in databases.
  4. 4. PURPOSE OF NLIDB  The purpose of natural language interfaces is to allow users to compose Question in natural language and receive responses.  Asking questions to databases in natural language like English is a very convenient and easy method of data access from database system especially for normal users who do not understand complicated database query languages such as SQL.  This enables a user to simply enter queries in English to the Natural Language Database Interface.
  5. 5. ARCHITECTURE OF NLIDB
  6. 6. SYSTEM ARCHITECTURE o Lexicon The lexicon supports the following two operations: 1.Given a word stem ws, retrieve the set of tokens which contain ws . 2.Given a token t, retrieve the set of database elements matching t. The names of all database elements are extracted and split into individual words. Each word is then stemmed and a corresponding set of synonyms is identified using a general purpose word ontology. Each database element is thus associated with a set of word stems and each word stem is in turn associated with set of synonyms.
  7. 7. TOKENIZER  The tokenizer’s input is a natural language question and its output is the set of all possible complete tokenization's of the question.  The tokenizer proceeds by stemming each word in the question, and the looking up in the lexicon the set of tokens containing the word stem.  For each potential token, the tokenizer checks whether the other words in the token are also present in the question.  Finally, the tokenizer also assigns to each token the types of database elements it could potentially match to (e.g., value , attribute, etc.).
  8. 8. MATCHER  In Matcher we reduce the problem of finding a semantic interpretation of ambiguous natural language tokens as database elements to a graph matching problem. Parser Plug in o It extracts attachment relationships between tokens from the parse tree. o The attachment relationships are used by the matcher in the generation of valid mappings(only semantic interpretations which satisfy the syntactic attachment constraints represent valid mappings).
  9. 9. QUERY GENERATOR  The query generator takes the database elements selected by the matcher and weaves them into a well-formed SQL query.  In the case of single-relation queries, this process is straightforward.  In the case of multi-relation queries, the generator adds join conditions to the WHERE clause, which reflect a join path that contains all the relations implicitly invoked by attributes in the query.  The generator generates a query for each possible join path and submits the queries to the equivalence checker.
  10. 10. EQUIVALENCE CHECKER  The equivalence checker tests whether there are multiple distinct solutions to the maxflow problem and whether these solutions translate into distinct SQL queries.  If this NLIDB finds two distinct SQL queries, it does not output an answer.
  11. 11. EXAMPLE o Natural Query What are the HP jobs on a Unix system? SYNTACTIC MARKERS (are , the , on , a) Tokens (job system HP Unix what) o SQL Query SELECT DISTINCT Description FROM JOB WHERE Platform =‘HP’ AND Company =‘Unix’;
  12. 12. WHERE NLIDB IS USED?? There are many applications that can take advantages of NLIDB. 1. In PDA(Personal Digital Assistance) and cell phone environments, the display screen is not as wide as a computer or a laptop. Filling a form that has many fields can be tedious: one may have to navigate through the screen, to scroll, to look up the scroll box values, etc. 2. Instead, with NLIDB, the only work that needs to be done is to type the question similar to the SMS (Short Messaging System).
  13. 13. ADVANTAGES  No Artificial Language  Simple, easy to use  Better for Some Questions  Fault tolerance  Easy to Use for Multiple Database Tables
  14. 14. DISADVANTAGES  Linguistic coverage is not obvious  Linguistic vs. conceptual failures  False expectations
  15. 15. CONCLUSION Though several NLIDB systems have also been developed so far for commercial use but the use of NLIDB systems is not wide-spread and it is not a standard option for interfacing to a database. This lack of acceptance is mainly due to the large number of deficiencies in the NLIDB system in order to understand a natural language.

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