Building Enriched Document Representations using Aggregated Anchor Text
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1 Building Enriched Document Representations using Aggregated Anchor Text Donald Metzler, Jasmine Novak, Hang Cui, and Srihari Reddy Yahoo! Labs 1
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3 The Importance of Anchor Text Anchor text is the most important source of evidence for web search ranking Even more important than link analysis techniques Queries and anchor text are lexically and semantically similar Anchor text is also useful for other web-based IR tasks Classification Content match (advertising on web pages) Image search Summarization 3
4 The Anchor Text Sparsity Problem Anchor text follows a power law A few web pages have a large amount of anchor text A large number of web pages have no anchor text Since anchor text is so important for many web-based IR tasks, web pages that have very little, or no anchor text may be unfavorably biased Web pages with no anchor text is less likely to be retrieved than pages with anchor text Matching ads to pages without anchor text is likely less effective than pages with anchor text Classification algorithms that use anchor text as a primary source of evidence may perform poorly on pages with no anchor text 4
5 Overcoming Anchor Text Sparsity The goal of this paper is to describe methods for overcoming the anchor text sparsity problem Three key steps Aggregate anchor text Weight aggregated anchor text Build enriched document representation We will also show that web search suffers from anchor text sparsity and that our proposed method for aggregating anchor text can help improve search relevance 5
6 Related Work Anchor text representations Using anchor text as meta-data [Brin and Page] Anchor text models [Fujii] Structured document retrieval BM25F [Robertson et al.] Mixtures of language models [Ogilvie and Callan] Approach is similar in spirit to, but differs from, the previously proposed approaches for spreading activation, link analysis, graph regularization, score aggregation, and term frequency aggregation Branded as different problems, but they all tackle similar problems We aggregate textual representations Similar idea was applied to image retrieval [Harmandas et al.] 6
7 A Few Definitions Hypertext link: consists of a destination URL and a short description called the anchor text <a href= >SIGIR 2009</a> Anchor text line: a unique piece of anchor text and its weight SIGIR 2009 (7.5), SIGIR (5.0), information retrieval (2.0) Internal/external inlinks: links that point to a target URL that originate from within/outside of the site of the target URL Internal/external anchor text: anchor text associated with internal/ external links 7
8 Aggregating Anchor Text Given a target URL u, we define the aggregated anchor text as the external anchor text of the internal inlinks of u The internal inlinks of u are typically created by the website publisher Tend to link related pages Can generally be trusted, although spammable The external anchor text captures what the world (beyond the publisher) thinks a page is about Fewer navigational (e.g., home, next ) anchor text lines than internal anchor text Spammable (e.g., miserable failure ) By semantic transitivity, the aggregated anchor text is likely to be a good descriptor of the target URL u 8
9 Weighting Aggregated Anchor Text Same line of anchor text, with different weights, may originate from multiple internal inlinks Apply standard result set fusion approaches to combine weights 9
10 Dancing at the Savoy Learn more about famous Savoy The Lindy hop was popularized in New York City dances in New York The Savoy, a dance hall in Harlem dancing to Lindy Hop 5 pages within the same site Lindy hop is a dance from New York Savoy In New York, dances like salsa, and the Lindy Hop swing dancing The Lindy hop
11 Dancing at the Savoy Learn more about famous Savoy The Lindy hop was popularized in New York City dances in New York swing dancing The Savoy, a dance hall in Harlem dancing to Lindy Hop 5 pages within the same site Lindy hop is a dance from New York Savoy In New York, dances like salsa, and the Lindy Hop MIN savoy ballroom: 1 lindy hop: 1 dances in new york: 2 The Lindy hop
12 Dancing at the Savoy Learn more about famous Savoy The Lindy hop was popularized in New York City dances in New York swing dancing The Savoy, a dance hall in Harlem dancing to Lindy Hop 5 pages within the same site Lindy hop is a dance from New York Savoy In New York, dances like salsa, and the Lindy Hop MAX savoy ballroom: 5 lindy hop: 1 dances in new york: 2 The Lindy hop
13 Dancing at the Savoy Learn more about famous Savoy The Lindy hop was popularized in New York City dances in New York swing dancing The Savoy, a dance hall in Harlem dancing to Lindy Hop 5 pages within the same site Lindy hop is a dance from New York Savoy In New York, dances like salsa, and the Lindy Hop MEAN savoy ballroom: 3 lindy hop: 0.5 dances in new york: 1 The Lindy hop
14 Dancing at the Savoy Learn more about famous Savoy The Lindy hop was popularized in New York City dances in New York swing dancing The Savoy, a dance hall in Harlem dancing to Lindy Hop 5 pages within the same site Lindy hop is a dance from New York Savoy In New York, dances like salsa, and the Lindy Hop SUM savoy ballroom: 6 lindy hop: 1 dances in new york: 2 The Lindy hop
15 Enriched Document Representations Aggregated anchor text can be used to build enriched document representations Three representations Combined: append aggregated anchor text lines to the end of the external anchor text section Backoff: same as combined, except we only append lines of aggregated anchor text that are not already part of the external anchor text field New section: create a new section within the document that contains the aggregated anchor text List not meant to be exhaustive, but rather to give an idea of how aggregated anchor text can be used to enhance document representations
16 Experiments Our goal is to show that anchor text sparsity is a problem for web search and that our aggregated anchor text approach can be used to improve search relevance Large-scale web test collection 22,822 queries 524,418 judged query/url pairs Judgments are on 5-point scale (Perfect, Excellent, Good, Fair, Bad) Aggregate anchor text across entire web graph Evaluate results using DCG@1, DCG@5, and NDCG Use modified version of BM25F for ranking Baseline uses all document fields available, including anchor text Parameters tuned to optimize NDCG All experiments use 2-fold cross validation 16
17 Overcoming Anchor Text Sparsity URLs with judgments (biased sample) Our method reduces the number of URLs with no anchor text by 38% Average of 34 lines of aggregated anchor text per URL Random sample of 1 million URLs 32,715 have external anchor text (about 3%) 50,127 have aggregated anchor text (about 5%) 43,841 of the 50,127 did not have external anchor text We can nearly double the number of URLs with anchor text Avg. number of anchor text lines per page increases from 1 to 11 17
18 Anchor Text Line Distribution
19 Web Search Results Using aggregated anchor text enriched document representations consistently and significantly improves retrieval effectiveness 19
20 Web Search Results (Continued ) Aggregated anchor text helps improve medium difficulty queries the most and (slightly) hurts easy queries, which are mostly navigational 20
21 Web Search Results (Continued ) Aggregated anchor text helps longer queries, especially 4+ word queries, which tend to be more difficult informational queries 21
22 Impact of Pruning Aggregated Anchor Text Baseline (not shown): Aggregated AT (all lines): Aggregated AT (1 line): Aggregated AT (100 lines)
23 Conclusions and Future Work Anchor text plays an important role in web-based search tasks Power law of anchor text distribution means that many pages that have no anchor text will unfairly biased Described a method for overcoming anchor text sparsity using the external anchor text of the internal inlinks Experimental results showed consistent and significant improvements when aggregated anchor text used to enrich web documents Future work Weight the aggregated anchor text based on how related it is to the target page Propagate anchor text weights using random walk model 23
24 Questions? 24
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