CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture:
Abstract: "In the Collaborative Requirements Capture Tool (CORECT) project, we are building a computer-based requirements capture tool for custom-built electronic testing systems. The requirements capture process involves the participation of a wide range of different types of people -- the cus...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Edinburgh
1994
|
| Schriftenreihe: | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper
674 |
| Schlagworte: | |
| Zusammenfassung: | Abstract: "In the Collaborative Requirements Capture Tool (CORECT) project, we are building a computer-based requirements capture tool for custom-built electronic testing systems. The requirements capture process involves the participation of a wide range of different types of people -- the customer, the salesperson, systems engineers, quality assurance, marketing, and so on. Our aim is to build a Computer-Supported Cooperative Working (CSCW) system which will allow these participants to define an Automatic Test System (ATS) collaboratively by adding data and making changes to an evolving design. The collected information about the design will form a large knowledge pool, all of which is pertinent to the design as a whole, but most of which is irrelevant to any particular person engaged in the design process. We will therefore be using natural language generation (NLG) technology to create documents from the central knowledge pool which are tailored to the particular information needs of the participants. These documents will give the users a snapshot of the developing design and will enable them to see how it can be improved and further developed. This paper gives an introduction to the problem we are tackling and how we are trying to solve it, and argues that combining CSCW for input with NLG for output in this way solves some of the problems which are encountered when trying to use either technology on its own." |
| Beschreibung: | 11 S. |
Internformat
MARC
| LEADER | 00000nam a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV010466547 | ||
| 003 | DE-604 | ||
| 005 | 20070413 | ||
| 007 | t | ||
| 008 | 951108s1994 |||| 00||| engod | ||
| 035 | |a (OCoLC)32841290 | ||
| 035 | |a (DE-599)BVBBV010466547 | ||
| 040 | |a DE-604 |b ger |e rakddb | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91G | ||
| 100 | 1 | |a Levine, John |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture |c John Levine and Chris Mellish |
| 264 | 1 | |a Edinburgh |c 1994 | |
| 300 | |a 11 S. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |v 674 | |
| 520 | 3 | |a Abstract: "In the Collaborative Requirements Capture Tool (CORECT) project, we are building a computer-based requirements capture tool for custom-built electronic testing systems. The requirements capture process involves the participation of a wide range of different types of people -- the customer, the salesperson, systems engineers, quality assurance, marketing, and so on. Our aim is to build a Computer-Supported Cooperative Working (CSCW) system which will allow these participants to define an Automatic Test System (ATS) collaboratively by adding data and making changes to an evolving design. The collected information about the design will form a large knowledge pool, all of which is pertinent to the design as a whole, but most of which is irrelevant to any particular person engaged in the design process. We will therefore be using natural language generation (NLG) technology to create documents from the central knowledge pool which are tailored to the particular information needs of the participants. These documents will give the users a snapshot of the developing design and will enable them to see how it can be improved and further developed. This paper gives an introduction to the problem we are tackling and how we are trying to solve it, and argues that combining CSCW for input with NLG for output in this way solves some of the problems which are encountered when trying to use either technology on its own." | |
| 650 | 7 | |a Computer software |2 sigle | |
| 650 | 4 | |a Natural language processing (Computer science) | |
| 700 | 1 | |a Mellish, Christopher S. |e Verfasser |4 aut | |
| 810 | 2 | |a Department of Artificial Intelligence: DAI research paper |t University <Edinburgh> |v 674 |w (DE-604)BV010450646 |9 674 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-006974515 | ||
Datensatz im Suchindex
| _version_ | 1804124899463135232 |
|---|---|
| any_adam_object | |
| author | Levine, John Mellish, Christopher S. |
| author_facet | Levine, John Mellish, Christopher S. |
| author_role | aut aut |
| author_sort | Levine, John |
| author_variant | j l jl c s m cs csm |
| building | Verbundindex |
| bvnumber | BV010466547 |
| ctrlnum | (OCoLC)32841290 (DE-599)BVBBV010466547 |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02548nam a2200313 cb4500</leader><controlfield tag="001">BV010466547</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20070413 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">951108s1994 |||| 00||| engod</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)32841290</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV010466547</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rakddb</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91G</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Levine, John</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture</subfield><subfield code="c">John Levine and Chris Mellish</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Edinburgh</subfield><subfield code="c">1994</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">11 S.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">University <Edinburgh> / Department of Artificial Intelligence: DAI research paper</subfield><subfield code="v">674</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Abstract: "In the Collaborative Requirements Capture Tool (CORECT) project, we are building a computer-based requirements capture tool for custom-built electronic testing systems. The requirements capture process involves the participation of a wide range of different types of people -- the customer, the salesperson, systems engineers, quality assurance, marketing, and so on. Our aim is to build a Computer-Supported Cooperative Working (CSCW) system which will allow these participants to define an Automatic Test System (ATS) collaboratively by adding data and making changes to an evolving design. The collected information about the design will form a large knowledge pool, all of which is pertinent to the design as a whole, but most of which is irrelevant to any particular person engaged in the design process. We will therefore be using natural language generation (NLG) technology to create documents from the central knowledge pool which are tailored to the particular information needs of the participants. These documents will give the users a snapshot of the developing design and will enable them to see how it can be improved and further developed. This paper gives an introduction to the problem we are tackling and how we are trying to solve it, and argues that combining CSCW for input with NLG for output in this way solves some of the problems which are encountered when trying to use either technology on its own."</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Computer software</subfield><subfield code="2">sigle</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Natural language processing (Computer science)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mellish, Christopher S.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="810" ind1="2" ind2=" "><subfield code="a">Department of Artificial Intelligence: DAI research paper</subfield><subfield code="t">University <Edinburgh></subfield><subfield code="v">674</subfield><subfield code="w">(DE-604)BV010450646</subfield><subfield code="9">674</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-006974515</subfield></datafield></record></collection> |
| id | DE-604.BV010466547 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T17:53:00Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-006974515 |
| oclc_num | 32841290 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM |
| owner_facet | DE-91G DE-BY-TUM |
| physical | 11 S. |
| publishDate | 1994 |
| publishDateSearch | 1994 |
| publishDateSort | 1994 |
| record_format | marc |
| series2 | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |
| spelling | Levine, John Verfasser aut CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture John Levine and Chris Mellish Edinburgh 1994 11 S. txt rdacontent n rdamedia nc rdacarrier University <Edinburgh> / Department of Artificial Intelligence: DAI research paper 674 Abstract: "In the Collaborative Requirements Capture Tool (CORECT) project, we are building a computer-based requirements capture tool for custom-built electronic testing systems. The requirements capture process involves the participation of a wide range of different types of people -- the customer, the salesperson, systems engineers, quality assurance, marketing, and so on. Our aim is to build a Computer-Supported Cooperative Working (CSCW) system which will allow these participants to define an Automatic Test System (ATS) collaboratively by adding data and making changes to an evolving design. The collected information about the design will form a large knowledge pool, all of which is pertinent to the design as a whole, but most of which is irrelevant to any particular person engaged in the design process. We will therefore be using natural language generation (NLG) technology to create documents from the central knowledge pool which are tailored to the particular information needs of the participants. These documents will give the users a snapshot of the developing design and will enable them to see how it can be improved and further developed. This paper gives an introduction to the problem we are tackling and how we are trying to solve it, and argues that combining CSCW for input with NLG for output in this way solves some of the problems which are encountered when trying to use either technology on its own." Computer software sigle Natural language processing (Computer science) Mellish, Christopher S. Verfasser aut Department of Artificial Intelligence: DAI research paper University <Edinburgh> 674 (DE-604)BV010450646 674 |
| spellingShingle | Levine, John Mellish, Christopher S. CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture Computer software sigle Natural language processing (Computer science) |
| title | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture |
| title_auth | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture |
| title_exact_search | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture |
| title_full | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture John Levine and Chris Mellish |
| title_fullStr | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture John Levine and Chris Mellish |
| title_full_unstemmed | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture John Levine and Chris Mellish |
| title_short | CORECT, combining CSCW with natural language generation for Collaborative Requirements Capture |
| title_sort | corect combining cscw with natural language generation for collaborative requirements capture |
| topic | Computer software sigle Natural language processing (Computer science) |
| topic_facet | Computer software Natural language processing (Computer science) |
| volume_link | (DE-604)BV010450646 |
| work_keys_str_mv | AT levinejohn corectcombiningcscwwithnaturallanguagegenerationforcollaborativerequirementscapture AT mellishchristophers corectcombiningcscwwithnaturallanguagegenerationforcollaborativerequirementscapture |