ACM Home Page
Please provide us with feedback. Feedback
Common sense investing: bridging the gap between expert and novice
Full text PdfPdf (385 KB)
Source Conference on Human Factors in Computing Systems archive
CHI '04 extended abstracts on Human factors in computing systems table of contents
Vienna, Austria
SESSION: Late breaking result papers table of contents
Pages: 1167 - 1170  
Year of Publication: 2004
ISBN:1-58113-703-6
Authors
Ashwani Kumar  MIT Media Laboratory, Cambridge, MA
Sharad C. Sundararajan  IBM, Design Automation, Fishkill, New York
Henry Lieberman  MIT Media Laboratory, Cambridge, MA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 33,   Citation Count: 1
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/985921.986015
What is a DOI?

ABSTRACT

In this paper, we describe Common Sense Investing (CSI), an interactive investment tool that uses a knowledge base of common sense statements in conjunction with domain knowledge to assist personal investors with their financial decisions, primarily asset-allocation. In interfaces that provide expert advice, one key problem is elicitation - how to ask questions that enable the expert model to make decisions, and at the same time, are understandable to the novice. The second problem is explanation - how to explain rationale behind expert decisions in terms that the user can understand. Many programs already encode expert models, but few have good models of novice knowledge, especially where broad knowledge of everyday life might bear on the subject. OMCSNet, a semantic network representation of the OpenMind Common Sense Knowledge Base, is the source of a wide range of facts about day-to-day life. CSI maps the user's goals, expressed in concepts from OMCSNet, to the expert's goals, expressed in technical financial terms. Instead of asking "What is your tolerance for risk?" where the user might not understand the concept of risk tolerance, we can ask, "Do you usually have a lot of credit card debt?" Aligning the expert's questions and decisions with common sense knowledge pertinent to the user increases the user's confidence in the ability of the system to meet their needs.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
 
3
 
4
 
5
 
6
 
7
8
9
10
 
11
 
12
Fillmore, Charles J. (1968): The case for case. In Bach and Harms (Ed.): Universals in Linguistic Theory (pp. 1--88), Holt, Rinehart, and Winston, New York.
 
13
Fillmore, Charles J. (1976): Frame semantics and the nature of language. In Annals of the New York Academy of Sciences: Conference on the Origin and Development of Language and Speech, Volume 280 (pp. 20--32).
 
14
Fillmore, Charles J. (1982): Frame semantics. In Linguistics in the Morning Calm (pp. 111--137), Hanshin Publishing Co., Seoul, South Korea.
 
15
Fillmore, Charles J. (1985): Frames and the semantics of understanding. In Quaderni di Semantica, Vol 6, No. 2 (pp. 222--254).
16
 
17
The Society of Mind, Marvin Minsky.
 
18
Hugo Liu and Henry Lieberman (2002). Robust photo retrieval using world semantics. In Proceedings of the LREC 2002 Workshop on Creating and Using Semantics for Information Retrieval and Filtering: State-of-the-art and Future Research, Las Palmas, Canary Islands, pp. 15--20.
19


Collaborative Colleagues:
Ashwani Kumar: colleagues
Sharad C. Sundararajan: colleagues
Henry Lieberman: colleagues