It is not uncommon to solve a problem based on the knowledge\nfrom a different domain. The paper presents a crowdsourcing based technique to\nhelp this analogy searching process. As the authors noted, such process is\nchallenging for both human and machine. The insight behind the proposed\napproach is representing a problem as the sets of structural relations between\nobjects involved, rather than the characteristics or attributes of the objects\nthemselves. Due to lack of textual similarity between analogical problems,\nconventional natural language techniques fall short. While it is equivalently\nhard for people as well, by introducing the structure identifying problem to a\nlarger scale, the crowd, people are able to find deeper structural analogies\nthan having to do that on their own. The crowdsourcing approach is evaluated by\ntwo experiments. Experiment one examines whether people\u2019s ability to find\nanalogical ideas is increased with the presence of structural schema of a\nproblem; experiment two confirms that having analogical ideas leads to better\nsolution than alternative methods. Overall, both experiments are successful and\ndemonstrate the potential of the proposed approach (presence of good schemas).\nYet, the paper fails to answer the question: how to reliably maintain good\nschemas from crowd workers in the first place?<\/p>\n\n\n\n
In my own experience, I often find analogical ideas useful\nto solve the problems I encountered. Therefore, I highly appreciate the\ncontribution and practical value of this paper. I especially appreciate the\nauthor\u2019s idea on how to computationally analyze analogical ideas. In terms of\ncognition, analogical thinking could be something that happens too fast for\neven the thinker to realize. By inducting analogical searching into a process\nof searching for the similarity of relational structures of source problem and\nrelating problem other than the attributes or characteristics of the involving\nobjects. Because the latter is certainly much harder to quantify and\ncomputationally analyze. <\/p>\n\n\n\n
The paper\u2019s focus lies in the two experiments that the\nauthor conducted to evaluate and validate their proposed crowdsourcing\napproach. Both of which seems to be thoroughly conducted. However, like many\nHCI experiments, some of the design choices do not have a super convincing\nbasis, unlike other CS experiments or evaluation process with objective\nquantitative measurements. For example, while the \u201cdetaching one object from\nanother\u201d is clear in the cat problem and dough problem, there is no argument\nthat the difference between these two problem won\u2019t make a difference in the\nparticipants\u2019 mental loop. I believe the authors must have thought about these\nlittle questions thoroughly, but documenting these things is a hard problem. <\/p>\n\n\n\n
I especially like that the authors noted the limitations at\nthe end. Because I was thinking about these limitations while I read the paper.\nIt seems like the authors have a focus on the research questions and are not\ntrying to cover the entire process, which I find valuable and practical in HCI\nstudies.<\/p>\n\n\n\n
When recruiting participants from the crowd, how can the\nauthors ensure the quality of the data gathered? Especially there are nonnative\nEnglish speakers? Or how can they be sure that people are honest with their\nbackground?<\/p>\n","protected":false},"excerpt":{"rendered":"
Summary It is not uncommon to solve a problem based on the knowledge from a different domain. The paper presents a crowdsourcing based technique to help this analogy searching process. As the authors noted, such process is challenging for both human and machine. The insight behind the proposed approach is representing a problem as the…<\/p>\n","protected":false},"author":261,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-116","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/posts\/116","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/users\/261"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/comments?post=116"}],"version-history":[{"count":1,"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/posts\/116\/revisions"}],"predecessor-version":[{"id":117,"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/posts\/116\/revisions\/117"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/media?parent=116"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/categories?post=116"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/ccc2019s\/wp-json\/wp\/v2\/tags?post=116"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}