Our research project seeks to improve the specification, design, and implementation of unsolicited reporting, mixed-initiative human-computer dialogs, such as those used in ATMs, airport and train kiosks, and smart phones and similar devices through the creative, and often non-traditional, use and application of concepts and techniques from programming languages such as currying and partial evaluation. We are optimisitc that the philosophical and conceptual connections between natural and programming languages suggest that additional concepts from programming languages, such as reflection, lazy evaluation, and (first-class) continuations, will find a natural place in our methodology. We see particular promise in the use of first-class continuations to elegantly model the transfer of control between dialog participants. Our long-term research goal is to develop and evaluate computational models, based on programming languages concepts, to simplify the complexity involved in designing and implementing mixed-initiative human-computer dialogs.

Below you will find links to our dialog modeling toolkit, publications, and the webpages of team members.

Dialog Modeling Toolkit

Our dialog modeling toolkit is available here.


Dialog Modeling Toolkit

Publications

Papers published by ACM Press are copyright by the ACM. Pre-print PDF versions of these papers are posted here by permission of ACM for your personal use. Not for redistribution.

Buck, J.W., Perugini, S., & Nguyen, T.V. (2018). Natural language, mixed-initiative personal assistant agents. In Kim, D.S., Lee, K., & Ushiama, T. (Eds.), Proceedings of the 12th International ACM Conference on Ubiquitous Information Management and Communication (IMCOM), 82:1-82:8. New York, NY: ACM Press. [DOI | PDF].

Buck, J.W., Perugini, S., & Nguyen, T.V. (2017). CSE: U: Mixed-initiative personal assistants. ACM Student Research Competition Grand Finals Candidates, 2016-2017; Undergraduate Student Winners. [PDF].

Buck, J.W. & Perugini, S. (2017). Mixed-initiative personal assistants [Extended Abstract]. In Barnes, T. & Garcia, D. (Eds.), Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE), 753-754. New York, NY: ACM Press. (First-place winner 2016-2017 ACM Student Research Competition.) [DOI | PDF].

Perugini, S. & Buck, J.W. (2016). A language-based model for specifying and staging mixed-initiative dialogs. In Campos, J.C. & Schmidt, A. (Eds.), Proceedings of the 8th International ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS), 204-216. New York, NY: ACM Press. [DOI | PDF].

Perugini, S. (2016). Mining mixed-initiative dialogs. In Su, S.-F. (Ed.), Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2287-2294. Los Alamitos, CA: IEEE Computer Society Press. [DOI | PDF].

Buck, J.W. & Perugini, S. (2016). A tool for staging mixed-initiative dialogs. In P. Phung, J. Shen, & M. Glass (Eds.), Proceedings of the 27th Modern Artificial Intelligence and Cognitive Science Conference (MAICS), 25–32. [eCommons PDF | CEUR-WS PDF].

Perugini, S. (2015). Staging mixed-initiative dialogs by program generation and transformation (Technical Report No. arXiv:1108.0476v5 [cs.PL]). Los Alamos, NM: Computing Research Repository (CoRR). [PDF | abstract].

Perugini, S. (2010). Personalization by website transformation: Theory and practice. Information Processing and Management, 46(3), 284-294 [DOI | PDF].

Perugini, S. & Ramakrishnan, N. (2010). Program transformations for information personalization. Computer Languages, Systems and Structures, 36(3), 223-249 [DOI | PDF].

Perugini, S. (2010). Supporting multiple access paths to objects in information hierarchies: Faceted classification, faceted search, and symbolic links. Information Processing and Management, 46(1), 22-43 [DOI | PDF].

Perugini, S. & Ramakrishnan, N. (2009). Exploring out-of-turn interactions with websites. Journal of Digital Information, 10(4) [abstract | HTML | PDF].

Stefaner, M., Ferré, S., Perugini, S., Koren, J. & Zhang, Y. (2009). User interface design. In G. Sacco & Y. Tzitzkas (Eds.), Dynamic taxonomies and faceted search: Theory, practice, and experience (Vol. 25, pp. 75-112). Berlin: Springer. (Invited submission.) [PDF].

Perugini, S. (2008). Symbolic links in the Open Directory Project. Information Processing and Management, 44(2), 910-930 [DOI | PDF].

Perugini, S., Anderson, T.J., & Moroney, W.F. (2007). A study of out-of-turn interaction in menu-based, ivr, voicemail systems. In In Gilmore, D. (Ed.), Proceedings of the 25th International ACM Conference on Human Factors in Computing Systems, 961-970. New York, NY: ACM Press. (Acceptance rate < 25%.) [DOI | PDF].

Perugini, S. & Ramakrishnan, N. (2007). Mining functional dependencies for flexible information access. Journal of the American Society for Information Science (JASIST), 58(12), 1805-1819. (In special issue of JASIST on Mining Web Resources for Enhancing Information Retrieval.) [DOI | PDF | HTML].

Perugini, S. & Ramakrishnan, N. (2006). Interacting with web hierarchies. IEEE IT Professional, 8(4), 19-28 [DOI | PDF].

Perugini, S. (2006). Real-time query expansion and procedural interfaces for information hierarchies. In Broder, A.Z. & Maarek, Y.S. (Eds.), Proceedings of the International ACM SIGIR Workshop on Faceted Search, 50-54 [PDF].

Perugini, S. & Ramakrishnan, N. (2005). A generative programming approach to interactive information retrieval: Insights and experiences. In Glück, R. & Lowry, M. (Eds.), Proceedings of the 4th International ACM Conference on Generative Programming and Component Engineering, LNCS 3676, 205-220. Berlin: Springer. [DOI | PDF].

Perugini, S. & Ramakrishnan, N. (2005). Personalization by Program Slicing. Journal of Object Technology, 4(3), 5-11. (Special issue on the 6th International ACM GPCE Young Researchers Workshop, Vancouver, Canada.) [PDF | HTML].

Narayan, M., Williams, C., Perugini, S., & Ramakrishnan, N. (2004). Staging transformations for multimodal web interaction management. In Najork, M. & Wills, C. (Eds.), Proceedings of the 13th International ACM World Wide Web Conference, 212-223. New York, NY: ACM Press. [DOI | PDF].

Perugini, S. McDevitt, K., Richardson, R., Pérez-Quiñones, M.A., Shen, R., Ramakrishnan, N., Williams, C., & Fox, E.A. (2004). Enhancing usability in CITIDEL: Multimodal, multilingual, and interactive visualization interfaces. In Lim, E.-P. & Christel (Eds.), Proceedings of the 4th International ACM/IEEE-CS Joint Conference on Digital Libraries, 315-324. New York, NY: ACM Press. [DOI | PDF].

Perugini, S. (2004). Program transformations for information personalization. Ph.D. Dissertation, Department of Computer Science, Virginia Tech. US Copyright Office Registration Number TX 6-040-012 [PDF | abstract].

Perugini, S., Ramakrishnan, N., & Fox, E.A. (2004). Automatically generating interfaces for personalized interaction with digital libraries (Technical Report No. cs.DL/0402022). Los Alamos, NM: Computing Research Repository [PDF | abstract].

Perugini, S. & Ramakrishnan, N. (2003). Personalizing web sites with mixed-initiative interaction. IEEE IT Professional, 5(2), 9-15. (Featured on the cover of the March-April issue and recognized in ACM TechNews Timely Topics, 5(490), Friday, May 2, 2003.) [DOI | PDF].

Perugini, S. & Ramakrishnan, N. (2003). Personalizing Interactions with Information Systems. In M.V. Zelkowitz (Ed.), Advances in Computers (pp. 323-382), 57: Information Repositories. Amsterdam: Academic Press. [PDF].

Capra, R., Narayan, M., Perugini, S. Ramakrishnan, N., & Pérez-Quiñones, M.A. (2003). The Staging Transformation Approach to Mixing Initiative. In Tecuci, G. (Ed.), Working Notes of the IJCAI Conference, Workshop on Mixed-Initiative Intelligent Systems, 23-29 [PDF].

Ramakrishnan, N. & Perugini, S. (2001). The partial evaluation approach to information personalization (Technical Report No. cs.IR/0108003). Los Alamos, NM: Computing Research Repository [PDF | abstract].

Perugini, S., Lakshminarayanan, P., & Ramakrishnan, N. (2000). Personalizing the GAMS cross-index (Technical Report No. TR-00-01). Blacksburg, VA: Department of Computer Science, Virginia Tech [PDF | abstract].


Faculty

  • Saverio Perugini (Associate Professor, Univ. of Dayton, Dept. of Computer Science)
  • Tam Nguyen (Assistant Professor, Univ. of Dayton, Dept. of Computer Science)
  • Benjamin Kunz (Associate Professor, Univ. of Dayton, Dept. of Psychology)

Students

  • Patrick Marsee (B.S., Computer Science, Univ. of Dayton, May 2018)
  • Vignesh Krishnaraja (M.C.S., Computer Science, Univ. of Dayton, August 2018)
  • Jacob Buck (B.S., Computer Science, Univ. of Dayton, May 2021)

Former student members

  • Joshua W. Buck (B.S., Computer Science, Univ. of Dayton, May 2017)

  • John-Paul V. Cresencia (M.C.S candidate, Computer Science, Univ. of Dayton)

  • Shuangyang Yang (M.S., Electro-optics, Univ. of Dayton, December 2008)
    Now a Ph.D. student in the Holcombe Dept. of Electrical and Computer Engineering at Clemson University.

  • Taylor J. Anderson (M.A., Psychology, Univ. of Dayton, September 2006)
    Thesis: A Study of Out-of-turn Interaction with a Voicemail System using Speech Recognition
    Now at SA Technologies in Marietta, GA.


  • © S. Perugini, Fall 2009-2019, University of Dayton.