arXiv subjects

Ricardo Baeza-Yates

Publications and source records attributed to Ricardo Baeza-Yates.

39 records · Page 3Linked to original sources

arXiv2013

Evolution of the Chilean Web: A Larger Study

In this paper we extend our previous and only study on the dynamics of the Chilean Web. This new study doubles the time period and to the best of our knowledge is the only study of its type known about any country in the Web. The new results corroborate the trends found before, in particular the exponential growth of the Web, and reinforce the conclusion that the Web is more chaotic than we would like. Hence, modeling most Web characteristics is not trivial.

cs.SI↗

arXiv2012

Learning to Rank Query Recommendations by Semantic Similarities

Logs of the interactions with a search engine show that users often reformulate their queries. Examining these reformulations shows that recommendations that precise the focus of a query are helpful, like those based on expansions of the original queries. But it also shows that queries that express some topical shift with respect to the original query can help user access more rapidly the information they need. We propose a method to identify from the query logs of past users queries that either focus or shift the initial query topic. This method combines various click-based, topic-based and session based ranking strategies and uses supervised learning in order to maximize the semantic similarities between the query and the recommendations, while at the same diversifying them. We evaluate our method using the query/click logs of a Japanese web search engine and we show that the combination of the three methods proposed is significantly better than any of them taken individually.

cs.AI↗

arXiv2010

Capacity Planning for Vertical Search Engines

Vertical search engines focus on specific slices of content, such as the Web of a single country or the document collection of a large corporation. Despite this, like general open web search engines, they are expensive to maintain, expensive to operate, and hard to design. Because of this, predicting the response time of a vertical search engine is usually done empirically through experimentation, requiring a costly setup. An alternative is to develop a model of the search engine for predicting performance. However, this alternative is of interest only if its predictions are accurate. In this paper we propose a methodology for analyzing the performance of vertical search engines. Applying the proposed methodology, we present a capacity planning model based on a queueing network for search engines with a scale typically suitable for the needs of large corporations. The model is simple and yet reasonably accurate and, in contrast to previous work, considers the imbalance in query service times among homogeneous index servers. We discuss how we tune up the model and how we apply it to predict the impact on the query response time when parameters such as CPU and disk capacities are changed. This allows a manager of a vertical search engine to determine a priori whether a new configuration of the system might keep the query response under specified performance constraints.

cs.IR↗