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- item-1 hasContent sergej-sizov.
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- item-2 hasContent bernhard-schueler.
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- 618 creator jiangong-zhang.
- 618 creator torsten-suel.
- 618 creator xiaohui-long.
- 618 type InProceedings.
- 618 label "Performance of Compressed Inverted List Caching in Search Engines".
- 618 sameAs 618.
- 618 abstract "Due to the rapid growth in the size of the web, web search engines are facing enormous performance challenges. The larger engines in particular have to be able to process tens of thousands of queries per second on tens of billions of documents, making query throughput a critical issue. To satisfy this heavy workload, search engines use a variety of performance optimizations including index compression, caching, and early termination. We focus on two techniques, inverted index compression and index caching, which play a crucial rule in web search engines as well as other high-performance information retrieval systems. We perform a comparison and evaluation of several inverted list compression algorithms, including new variants of existing algorithms that have not been studied before. We then evaluate different inverted list caching policies on large query traces, and finally study the possible performance benefits of combining compression and caching. The overall goal of this paper is to provide an updated discussion and evaluation of these two techniques, and to show how to select the best set of approaches and settings depending on parameter such as disk speed and main memory cache size.".
- 618 hasAuthorList authorList.
- 618 hasTopic World_Wide_Web.
- 618 isPartOf proceedings.
- 618 keyword "Index Caching".
- 618 keyword "Index Compression".
- 618 keyword "Inverted Index".
- 618 keyword "Search Engine".
- 618 title "Performance of Compressed Inverted List Caching in Search Engines".
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- item-1 hasContent jiangong-zhang.
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- 625 creator deepayan-chakrabarti.
- 625 creator kunal-punera.
- 625 creator ravi-kumar.
- 625 type InProceedings.
- 625 label "A graph-theoretic approach to webpage segmentation".
- 625 sameAs 625.
- 625 abstract "We consider the problem of segmenting a web page into visually and semantically cohesive pieces. Our approach is based on formulating an appropriate optimization problem on weighted graphs, where the weights capture if two nodes in the DOM tree should be placed together or apart in the segmentation; we present a learning framework to learn these weights from manually labeled data in a principled manner. Our work is a significant departure from previous heuristic and rule-based solutions to the segmentation problem. The results of our empirical analysis bring out interesting aspects of our framework, including variants of the optimization problem and the role of learning.".
- 625 hasAuthorList authorList.
- 625 hasTopic World_Wide_Web.
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- 625 keyword "correlation clustering".
- 625 keyword "energy minimization".
- 625 keyword "graph cuts".
- 625 keyword "webpage sectioning".
- 625 keyword "webpage segmentation".
- 625 title "A graph-theoretic approach to webpage segmentation".
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- item-1 hasContent deepayan-chakrabarti.
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- item-3 hasContent kunal-punera.
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- 638 creator deepak-ravichandran.
- 638 creator jay-yagnik.
- 638 creator mohamed-aly.
- 638 creator rohan-seth.
- 638 creator shankar-kumar.
- 638 creator shumeet-baluja.
- 638 creator sivakumar-d.
- 638 creator yushi-jing.
- 638 type InProceedings.
- 638 label "Video Suggestion and Discovery for YouTube: Taking Random Walks Through the View Graph".
- 638 sameAs 638.
- 638 abstract "The rapid growth of the number of videos in YouTube provides enormous potential for users to find content of interest to them. Unfortunately, given the difficulty of searching videos, the size of the video repository also makes the discovery of new content a daunting task. In this paper, we present a novel method based upon the analysis of the entire user--video graph to provide personalized video suggestions for users. The resulting algorithm, termed Adsorption, provides a simple method to efficiently propagate preference information through a variety of graphs. We extensively test the results of the recommendations on a three month of live-data from YouTube.".
- 638 hasAuthorList authorList.
- 638 hasTopic World_Wide_Web.
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- 638 keyword "Graph Algorithms".
- 638 keyword "Label Propagation".
- 638 keyword "Recommendation Algorithms".
- 638 keyword "Social Networks".
- 638 keyword "Video".