González-Ibáñez, R.; Shah, C.; White, R.W.: Capturing 'Collabportunities' : a method to evaluate collaboration opportunities in information search using pseudocollaboration (2015)
0.01
0.007890998 = product of:
0.015781997 = sum of:
0.015781997 = product of:
0.031563994 = sum of:
0.031563994 = weight(_text_:b in 2167) [ClassicSimilarity], result of:
0.031563994 = score(doc=2167,freq=2.0), product of:
0.16126883 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.045518078 = queryNorm
0.19572285 = fieldWeight in 2167, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.0390625 = fieldNorm(doc=2167)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- In explicit collaborative search, two or more individuals coordinate their efforts toward a shared goal. Every day, Internet users with similar information needs have the potential to collaborate. However, online search is typically performed in solitude. Existing search systems do not promote explicit collaborations, and collaboration opportunities (collabportunities) are missed. In this article, we describe a method to evaluate the feasibility of transforming these collabportunities into recommendations for explicit collaboration. We developed a technique called pseudocollaboration to evaluate the benefits and costs of collabportunities through simulations. We evaluate the performance of our method using three data sets: (a) data from single users' search sessions, (b) data with collaborative search sessions between pairs of searchers, and (c) logs from a large-scale search engine with search sessions of thousands of searchers. Our results establish when and how collabportunities would significantly help or hinder the search process versus searches conducted individually. The method that we describe has implications for the design and implementation of recommendation systems for explicit collaboration. It also connects system-mediated and user-mediated collaborative search, whereby the system evaluates the likely benefits of collaborating for a search task and helps searchers make more informed decisions on initiating and executing such a collaboration.
