Rank retrieval model

presents the following content: Chapter 1: introduction; chapter 2: data, information, and knowledge; chapter 3: representation of information; chapter 4: attribute content and values; chapter 5: models of virtual data structure; chapter 6: the physical structure of data; chapter 7: querying the information retrieval system; chapter 8: interpretation and execution of query statements; chapter 9: text searching; chapter 10: system-computed relevance and ranking; chapter 11: search feedback and iteration; chapter 12: multi-database searching and mapping; chapter 13: search strategy; chapter 1...

391p runthenight08 12-04-2023 5 2   Download

Information retrieval techniques: Lecture 3. The main topics covered in this chapter include: boolean retrieval model; rank retrieval model; information retrieval ingredients; westlaw; documents representation; query formulation; query processing;... Please refer to the content of document.

17p tieuvulinhhoa 22-09-2022 9 4   Download

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data.

8p vioklahoma2711 19-11-2020 8 0   Download

This paper investigates an application of the ranked region algebra to information retrieval from large scale but unannotated documents. We automatically annotated documents with document structure and semantic tags by using taggers, and retrieve information by specifying structure represented by tags and words using ranked region algebra. We report in detail what kind of data can be retrieved in the experiments by this approach.

8p bunbo_1 17-04-2013 40 2   Download

We present a study aimed at investigating the use of semantic information in a novel NLP application, Electronic Career Guidance (ECG), in German. ECG is formulated as an information retrieval (IR) task, whereby textual descriptions of professions (documents) are ranked for their relevance to natural language descriptions of a person’s professional interests (the topic).

8p hongvang_1 16-04-2013 46 1   Download

Statistical language modeling (SLM) has been used in many different domains for decades and has also been applied to information retrieval (IR) recently. Documents retrieved using this approach are ranked according their probability of generating the given query. In this paper, we present a novel approach that employs the generalized Expectation Maximization (EM) algorithm to improve language models by representing their parameters as observation probabilities of Hidden Markov Models (HMM).

9p hongphan_1 15-04-2013 68 2   Download

In Cross-Language Information Retrieval (CLIR), Out-of-Vocabulary (OOV) detection and translation pair relevance evaluation still remain as key problems. In this paper, an English-Chinese Bi-Directional OOV translation model is presented, which utilizes Web mining as the corpus source to collect translation pairs and combines supervised learning to evaluate their association degree.

4p hongphan_1 15-04-2013 58 1   Download

Topical blog post retrieval is the task of ranking blog posts with respect to their relevance for a given topic. To improve topical blog post retrieval we incorporate textual credibility indicators in the retrieval process. We consider two groups of indicators: post level (determined using information about individual blog posts only) and blog level (determined using information from the underlying blogs). We describe how to estimate these indicators and how to integrate them into a retrieval approach based on language models. ...

9p hongphan_1 15-04-2013 44 1   Download

The use of phrases in retrieval models has been proven to be helpful in the literature, but no particular research addresses the problem of discriminating phrases that are likely to degrade the retrieval performance from the ones that do not. In this paper, we present a retrieval framework that utilizes both words and phrases flexibly, followed by a general learning-to-rank method for learning the potential contribution of a phrase in retrieval.

9p hongphan_1 14-04-2013 46 3   Download