Google Inc.

International Business Machines Corporation

Hazem Elmeleegy

Jayant Madhavan

Alon Yitzchak Halevy

Rama Kalyani T Akkiraju

Richard Thomas Goodwin

Anca-Andreea Ivan

List information can be extracted into database tables. A number of fields are independently determined for items in list. A number of database table columns are determined from most common number of list item fields. New fields are determined for items with more fields than database columns. Null fields are inserted into items with fewer fields than database columns. Information from items having the same number of fields as database columns is written to database table rows. Information from each field is written to a corresponding database table column. Streaks of poorly matching cells in a database table row are determined. Streak cells are merged and new cells are determined. Null cells are inserted if number of new cells is less than number of cells in the streak. Information from the new cells is written to the table row and columns that define the streak.

Harvesting relational tables from lists on the web

Computer implemented methods and apparatus for extracting list information into database tables. A number of fields are independently determined for items in list. A number of database table columns are determined from most common number of list item fields. New fields are determined for items with more fields than database columns. Null fields are inserted into items with fewer fields than database columns. Information from items having the same number of fields as database columns is written to database table rows. Information from each field is written to a corresponding database table column. Streaks of poorly matching cells in a database table row are determined. Streak cells are merged and new cells are determined. Null cells are inserted if number of new cells is less than number of cells in the streak. Information from the new cells is written to the table row and columns that define the streak.

A recommendation system exploits a repository of mashups to provide design-time assistance to the user through relevant suggestions as to what outputs can be generated along with the best plans to generate those outputs. An output ranker ranks the outputs of the system base on their popularity scores, and a planner uses metric planning algorithms and a configurable utility function. The system takes into account popularity and semantic similarity when recommending services and sources.

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West Lafayette, IN, United States of America

Hazem Elmeleegy