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Smoothing Click Counts for Aggregated Vertical Search
[chapter]
2011
Lecture Notes in Computer Science
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In this work, we focus on mitigating the negative effect of rank cut for aggregated vertical searches. We introduce a technique for smoothing click counts based on spectral graph analysis. ...
Using real clickthrough data from a vertical recorded in an aggregated search environment, we show empirically that clickthrough data smoothed by this technique is effective for improving the vertical ...
Acknowledgments This work was supported in part by the Center for Intelligent Information Retrieval, in part by NHN Corp. and in part by NSF grant #IIS-0711348. ...
doi:10.1007/978-3-642-20161-5_39
fatcat:3j74o4muc5d2nnez6cxighblty
Detecting Multilingual and Multi-Regional Query Intent in Web Search
2011
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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We introduce a query intent probabilistic model, whose input is the number of clicks on documents from different regions and in different language, while the output of this model is a smoothed probabilistic ...
detection for 18%. ...
(Li, Wang, and Acero 2008) use click graphs to improve coverage of query intent classifiers for vertical search applications, such as, product search and job search. ...
doi:10.1609/aaai.v25i1.8074
fatcat:mdifxctkmnh6xamhii7oy3dp5y
Evaluating aggregated search using interleaving
2013
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13
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All this makes our proposed interleaving algorithm an essential tool for comparing IR systems with complex aggregated pages. ...
Such a system is called an aggregated or federated search system. Because search engines evolve over time, their results need to be constantly evaluated. ...
We thank Filip Radlinski for his detailed feedback on a draft of this paper. ...
doi:10.1145/2505515.2505698
dblp:conf/cikm/ChuklinSHSR13
fatcat:xpd5elvxvncllcygw7v67xwmwy
Improving local search ranking through external logs
2011
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11
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We evaluate our techniques on both human-judged relevance data as well as click-through data from a commercial local search engine. ...
The signals used for ranking in local search are very different from web search: in addition to (textual) relevance, measures of (geographic) distance between the user and the search result, as well as ...
To assess these signals directly on the basis of click information derived from the local search vertical is very difficult, in part due to the position bias of the click signal [21] . ...
doi:10.1145/2009916.2010021
dblp:conf/sigir/BerberichKLZ11
fatcat:xoxuidl3bjbdfcvslusxm56ham
KDEIM at NTCIR-12 IMine-2 Search Intent Mining Task: Query Understanding through Diversified Ranking of Subtopics
2016
NTCIR Conference on Evaluation of Information Access Technologies
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We propose a method that extracts subtopics by leveraging the query suggestions from search engines. ...
The best performance of our method achieves an I-rec of 0.7557, a D-nDCG of 0.6644, a D#-nDCG of 0.7100, and a QU-score of 0.5057 at the cutoff rank 10 for query understanding task. ...
According to this intuition, we make use of search engine hit count to estimate features including normalized hit count (NHC), point-wise mutual information (PMI), and word cooccurrence (WC). ...
dblp:conf/ntcir/UllahSA16
fatcat:2kdz5biiwjfb5iawyzqgitxpau
Learning to Rank for Educational Search Engines
2021
IEEE Transactions on Learning Technologies
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click count for a given query. ...
models neither for a general Web search engine nor for a vertical. ...
doi:10.1109/tlt.2021.3075196
fatcat:buud677r3basli6e7qdkpevoqm
Learning to aggregate vertical results into web search results
2011
Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11
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Aggregated search is the task of integrating results from potentially multiple specialized search services, or verticals, into the Web search results. ...
Learning models to aggregate results from multiple verticals is associated with two major challenges. ...
PROBLEM DEFINITION At query time, the aggregated search system issues the query to the Web search engine and to those verticals selected, which we refer to as the candidate verticals. ...
doi:10.1145/2063576.2063611
dblp:conf/cikm/ArguelloDC11
fatcat:x4bi7owrdbd65arqv4o643q6tu
Manual S01: Manual and example application to model 'Core-Areas' (Optimally Describing Isolines) using MapInfo & Vertical Mapper from Approaching prehistoric demography: proxies, scales and scope of the Cologne Protocol in European contexts
2020
figshare.com
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Set Nugget to 0.To facilitate the search for the first plateau, we can enlarge the Semivariogram View by clicking right on the diagram, select Maximize and zoom in.The maximised Semivariogram Views should ...
Site aggregation follows the same procedure as described in Step 4: "Aggregation of vertices". ...
doi:10.6084/m9.figshare.13142915.v1
fatcat:42sbnzx4e5gqbdkk7kqv63lox4
Mining the search trails of surfing crowds
2008
Proceeding of the 17th international conference on World Wide Web - WWW '08
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in learning to rank for Web search. ...
We present heuristic and probabilistic algorithms that rely on such datasets for suggesting authoritative websites for search queries. ...
Figure 1 : 1 Search trail example
Figure 2 : 2 Random walks for search trailswhere n(di,tj) = q d i s.t.t j ∈q f (q di)is again the aggregated count for document di reached from queries containing term ...
doi:10.1145/1367497.1367505
dblp:conf/www/BilenkoW08
fatcat:4oi3iayanjh2bnoya4cw3ewn3u
On composition of a federated web search result page
2011
Proceedings of the fourth ACM international conference on Web search and data mining - WSDM '11
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these engines are then aggregated and composed into a search result page (SERP) and presented to the user. ...
Modern web search engines are federated -a user query is sent to the numerous specialized search engines called verticals like web (text documents), News, Image, Video, etc. and the results returned by ...
Perhaps some of the query classifier features also help in smoothing the models by aggregating over tail queries in specific categories. ...
doi:10.1145/1935826.1935922
dblp:conf/wsdm/PonnuswamiPWGK11
fatcat:bfyp4vic2zf5pka7f35o3stgte
Incorporating the surfing behavior of web users into pagerank
2013
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13
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Our empirical results indicate that the proposed model leads to better estimation of page importance according to an evaluation metric that relies on user click feedback obtained from web search query ...
In large-scale commercial web search engines, estimating the importance of a web page is a crucial ingredient in ranking web search results. ...
Figure 1 : 1 Visit count of a URL in the browsing data versus its click count in search results.
Figure 2 : 2 Distribution of URL visit counts in toolbar data. ...
doi:10.1145/2505515.2505668
dblp:conf/cikm/AshyralyyevCA13
fatcat:m7iz6pnc35dbvaqwga466eabq4
Optimal rare query suggestion with implicit user feedback
2010
Proceedings of the 19th international conference on World wide web - WWW '10
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Unlike the Rocchio algorithm, our learning process does not involve the content of the URLs but simply leverages the click and skip counts in the query-URL bipartite graphs. ...
Consequently, our model is capable of scaling up to the need of commercial search engines. ...
Essentially, the backward model can be treated as a nor- malization on the document clicks instead of query counts. ...
doi:10.1145/1772690.1772782
dblp:conf/www/SongH10
fatcat:b2m6gsugdfajddkzdaialokb2m
Extracting Events from Spatial Time Series
2010
2010 14th International Conference Information Visualisation
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For example, data about visits of Web sites or use of various terms in Web searches are available in the form of counts by time intervals. ...
The first one contains weekly aggregates of the Google search data relevant to flu 1 by the states of the USA starting from 28/09/2003. ...
doi:10.1109/iv.2010.17
dblp:conf/iv/AndrienkoAMMP10
fatcat:kua75hw7arhxfl7jgfr4cduh3i
A semi-supervised approach to modeling web search satisfaction
2012
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12
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We show that the proposed model outperforms previous methods for modeling search success using labeled data. ...
Web search is an interactive process that involves actions from Web search users and responses from the search engine. ...
Page views included query submission, search result clicks, navigation beyond the search results page originating from clicks on links in a search result, and clicks on other search engine features (e.g ...
doi:10.1145/2348283.2348323
dblp:conf/sigir/Hassan12
fatcat:3afjszmsjncixe5qoflhmcndjq
A task level metric for measuring web search satisfaction and its application on improving relevance estimation
2011
Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11
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Understanding the behavior of satisfied and unsatisfied Web search users is very important for improving users search experience. ...
We use our user satisfaction model to distinguish between clicks that lead to satisfaction and clicks that do not. ...
We used smoothing to account for any data scarcity. We build two such models. ...
doi:10.1145/2063576.2063599
dblp:conf/cikm/HassanSH11
fatcat:pwvqpinlkjhuzhb3nxb7zosawy
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