Wednesday, 20 November 2013

DIAGRAM-2

USER ACTION



DIAGRAM-1


FLOW CHART OF DYNAMIC QUERY FORM

-It starts with a basic query form which contains very few primary attributes of the database. 

-The basic query form is then enriched iteratively via the  interactions between the user and our system until the user  is    satisfied with the query results.




LITERATURE SURVEY-REFERENCE PAPER-7

Usher:Improving Data Quality with Dynamic Forms:Kuang Chen ,Harr Chen, Neil Conway , Joseph M. Hellerstein , Tapan S. Parikh 

-Data quality is a critical problem in modern db.

-It is used of detecting and mitigating errors.


-Here present USHER, an end to end system for form design,entry & data quality assurance.


-It learns a probabilistic model over question of the form.


-It mainly done in two step,First by learning the  relationship between form question via structure    learning &  second by estimating the parameters of a Bayesian network.


-Which help to generate predictions &error probabilities

  for the form.

-This develop an adaptive form system for data entry,which can be dynamically changed according to  previous data input by the user.


http://db.cs.berkeley.edu/papers/icde10-usher.pdf

Tuesday, 19 November 2013

LITERATURE SURVEY- REFERENCE PAPER-6

Building dynamic faceted search systems over databases, S. B. Roy, H. Wang, U. Nambiar, G. Das, and M. K. Mohania :

Domain independent system that provides effective minimum-effort based faceted search solution over enterprise db.

Present relevent facetes for the users according to their navigation path. 

Dynamic faceted search engine is similar to our dynamic query form if we only consider selection component in a query.

Besides selection, db has other important component called projection component.

Projection component control the output of the query form.

Dynacet is a middleware system that sit between user and the db & dynamically suggest facetes for drilling db.

Here front end of the system is a web-based user interface enable user to build queries.

LITERATURE SURVEY - REFERENCE PAPER-5

5). Query Recommendations for interactive db exploration G. Chatzopoulou, 
      M. Eirinaki and   N. Polyzotis:



         - Here introduce collaborative approach to recommend db query form for db exploration.
        
         - Treat SQL as items , recommend similar queries to related users.

To generate recommendations, our frame work generate a predicted summary.This summary captures predicted degree of interest of active user with respect to all the parts of db.
Using this predicted summary, the framework construct queries that cover the subset of db with the highest predicted importance.
      
      Overall frame work consist of three components:

            (a). Construct session summary for each user based on query.

            (b). Computation of predicted summary based on active user &
                   summaries of part user

            (c). Generation of queries based on predicted summary.
       
Here represent a query recommendation frame work supporting the interactive exploration of relational db & an instantiation of this frame work based on user based collaborative filtering.


        DISADVANTAGE

           Do not consider the goodness of query result.

Monday, 18 November 2013

LITERATURE SURVEY -REFERENCE PAPER -4


4). Combining keyword search and form for adhoc querying of db, E.chu,A.Baid,X.chai

    A. Doan and  J.F. Naughton:

                     - Automatically generate a lot of query form in advance.

                     - User input several keyword to find relevent query form.

                     - It works well in db have rich textual information.

                     - Here query rewrite by mapping data value to schema value
                       during keyword search.

                     - Display the returned form as a flat list.

   DISADVANTAGE

                  It is not appropriate when user does not have a concrete keyword
         to describe query at the begining, especially for numeric attributes.

    Given a keyword query, augment user queries with form terms.
    Form terms such as schema, terms,SQL, Keywords & Natural language
    description.

    Retrive form that containing form term.
    
    To implement this, use two inverted indexes: one for data set
    other for set of forms.

     The first index is called Data index,takes in a term and return a set of
     < tuple_id, table> pair.
     tuple id is the primary key of tuple.
     table is the name of the table containing the tuple.

     Second index called Form index. 
     It returns form id.

     Here use  DOUBLE- INDEX OR approach.Include two step.
     First step is query rewrite.
     Second step is simply prob Form index with terms in FormTerms.

     It also uses DOUBLE-INDEX AND approach.
     This generate new queries by taking term from each bucket of
     FormTerm.Then evaluate query with semantic AND, then union result.

     DOUBLE-INDEX JOIN approach, estimate "dead forms" with extra probe to DataIndex.

     Rank according to user interest.
    
                    

              

LITERATURE SURVEY- REFERENCE PAPER -3

 3).Automating the design and construction of query form,M.Jayapandian,H.V.Jagadish

               - Proposed an automatic approach.

               - Work-load driven method.

               - Applies CLUSTERING ALGORITHM on historical queries.

               - Generate query form based on representative queries.

      DISADVANTAGES
               
         - If db schema is large and complex, user queries quit diverse.
   
         - If we generate lots of query form in advance, there are still user queries
           that is not satisfied by one of the query form.

  Here develop a mechanism to overcome the challenge to limit the usefulness of form.
  
  Here introduce a form generation algorithm, generate form automatically in expected 
  query work load .

  To control a form's readability, introduce a FORM COMPLEXITY THRESHOLD.

  FCT is satisfied by splitting query cluster covered by complex form to 
  smaller cluster covered by simpler form.

  To measure how useful a form, here define expressivity.

  http://www.eecs.umich.edu/db/files/icde06form.pdf