Details
| Original language | English |
|---|---|
| Title of host publication | WebSci 2017 - Proceedings of the 2017 ACM Web Science Conference |
| Pages | 289-298 |
| Number of pages | 10 |
| ISBN (electronic) | 9781450348966 |
| Publication status | Published - Jun 2017 |
| Event | 9th ACM Web Science Conference, WebSci 2017 - Troy, United States Duration: 25 Jun 2017 → 28 Jun 2017 |
Abstract
Web archives have been instrumental in digital preservation of the Web and provide great opportunity for the study of the societal past and evolution. These Web archives are massive collections, typically in the order of terabytes and petabytes. Due to this, search and exploration of archives has been limited as full-text indexing is both resource and computationally expensive. We identify that for typical access methods to archives, which are navigational and temporal in nature, we do not always require indexing full-text. Instead, meaningful text surrogates like anchor texts already go a long way in providing meaningful solutions and can act as reasonable entry points to exploring Web archives. In this paper, we present a new approach to searching Web archives based on temporal link graphs and corresponding anchor texts. Departing from traditional informational intents, we show how temporal anchor texts can be effective in answering queries beyond purely navigational intents, like finding the most central webpages of an entity in a given time period. We propose indexing methods and a temporal retrieval model based on anchor texts. Further, we discuss several interesting search results as well as one experiment in which we demonstrate how such results can be integrated in a data processing workflow to scale up to thousands of pages. In this analysis we were able to replicate results reported by an offline study, showing that restaurant prices indeed increased in Germany when the Euro was introduced as Europe's currency.
Keywords
- Big data analysis, Temporal information retrieval, Web archives
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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WebSci 2017 - Proceedings of the 2017 ACM Web Science Conference. 2017. p. 289-298.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Exploring Web Archives Through Temporal Anchor Texts
AU - Holzmann, Helge
AU - Nejdl, Wolfgang
AU - Anand, Avishek
PY - 2017/6
Y1 - 2017/6
N2 - Web archives have been instrumental in digital preservation of the Web and provide great opportunity for the study of the societal past and evolution. These Web archives are massive collections, typically in the order of terabytes and petabytes. Due to this, search and exploration of archives has been limited as full-text indexing is both resource and computationally expensive. We identify that for typical access methods to archives, which are navigational and temporal in nature, we do not always require indexing full-text. Instead, meaningful text surrogates like anchor texts already go a long way in providing meaningful solutions and can act as reasonable entry points to exploring Web archives. In this paper, we present a new approach to searching Web archives based on temporal link graphs and corresponding anchor texts. Departing from traditional informational intents, we show how temporal anchor texts can be effective in answering queries beyond purely navigational intents, like finding the most central webpages of an entity in a given time period. We propose indexing methods and a temporal retrieval model based on anchor texts. Further, we discuss several interesting search results as well as one experiment in which we demonstrate how such results can be integrated in a data processing workflow to scale up to thousands of pages. In this analysis we were able to replicate results reported by an offline study, showing that restaurant prices indeed increased in Germany when the Euro was introduced as Europe's currency.
AB - Web archives have been instrumental in digital preservation of the Web and provide great opportunity for the study of the societal past and evolution. These Web archives are massive collections, typically in the order of terabytes and petabytes. Due to this, search and exploration of archives has been limited as full-text indexing is both resource and computationally expensive. We identify that for typical access methods to archives, which are navigational and temporal in nature, we do not always require indexing full-text. Instead, meaningful text surrogates like anchor texts already go a long way in providing meaningful solutions and can act as reasonable entry points to exploring Web archives. In this paper, we present a new approach to searching Web archives based on temporal link graphs and corresponding anchor texts. Departing from traditional informational intents, we show how temporal anchor texts can be effective in answering queries beyond purely navigational intents, like finding the most central webpages of an entity in a given time period. We propose indexing methods and a temporal retrieval model based on anchor texts. Further, we discuss several interesting search results as well as one experiment in which we demonstrate how such results can be integrated in a data processing workflow to scale up to thousands of pages. In this analysis we were able to replicate results reported by an offline study, showing that restaurant prices indeed increased in Germany when the Euro was introduced as Europe's currency.
KW - Big data analysis
KW - Temporal information retrieval
KW - Web archives
UR - http://www.scopus.com/inward/record.url?scp=85026767746&partnerID=8YFLogxK
U2 - 10.1145/3091478.3091500
DO - 10.1145/3091478.3091500
M3 - Conference contribution
AN - SCOPUS:85026767746
SP - 289
EP - 298
BT - WebSci 2017 - Proceedings of the 2017 ACM Web Science Conference
T2 - 9th ACM Web Science Conference, WebSci 2017
Y2 - 25 June 2017 through 28 June 2017
ER -