Query-dependent ranking and its asymptotic properties

Contextualized Web Search: Query-dependent Ranking and Social Media Search

Rankom: a Query-dependent Ranking System for Information Retrieval

Ranking plays an important role in information retrieval, aiming to sort the documents retrieved for a given query in the descending order of relevance. Recently, many approaches based on the idea of “learning to rank” have been proposed for doing ranking. Most of them consider all the documents of the training queries to build a static, query-independent ranking model. In this paper, we propos...

A Simple Linear Ranking Algorithm Using Query Dependent Intercept Variables

The LETOR website contains three information retrieval datasets used as a benchmark for testing machine learning ideas for ranking. Algorithms participating in the challenge are required to assign score values to search results for a collection of queries, and are measured using standard IR ranking measures (NDCG, precision, MAP) that depend only the relative score-induced order of the results....

extraction and acetylation of purified trypsin from bovin pancreas and study of some its physico-chemical properties

آنزیم تریپسین در شرایط قلیایی ناپایدار می باشد .و فعالیت پروتئولیتیکی تریپسین منجربه خود هضمی آن در جایگاههای خاصی می گردد. بنابر این آنزیمی با ناپایداری بالا محسوب میگردد. در سالهای اخیر موفق شدند که با ایجاد تغیرات شیمیایی با اضافه کردن فلزات خاص ، کلسیم و یا عمل استیلاسیون منجر به افزایش پایداری آنزیم تریپسین گردند. مطالعات در حال حاضر نشان می دهد که تریپسین استیله شده فعالیت آنزیمی خود را ...

Query Ranking in Information Integration

Given the growing number of structured and evolving online repositories, the need for lightweight information integration has increased in the past years. We have developed an integration approach which relies on partial mappings for query rewriting and combines them with a controlled way of relaxation. In this paper we propose a novel approach for ranking results of such rewritten and relaxed ...