I want to rank documents for given queries The ranking have to be implemented in two steps: 1)First pass retrieval: Use Anserini SimpleSearcher to rank all documents for a given query 2)Second pass retrieval: Re-rank top-100 documents from the 1st pass retrieval using a retrieval model from pyserini.search import SimpleSearcher results =  searcher = ..
I am wanting to build an LTR model on the query dataset: The aim is to train a model and produce a tsv result file. Here is the sample data frame. | Query_id var1 var2 var3 Docid Label 0 77d4aadf 0.625676 0.192133 0.598358 9d8a1f461ed5 0 1 77d4aadf 0.000000 0.650000 0.148386 fc6bf04dd03b 2 2 77d4aadf 0.000000 ..
I have been exploring this problem a lot about just using the website url to tag or cluster them as per their business domain. For example: amazon.com => e-commerce bbc.co.uk => news Adidas.com => sports apparel or lets say Amazon.com/xbox => gadget I have read through some research papers which try to cluster using different ..
I am using Google Colab for apache solr 8.5.0 server implementation of Content Based Image Retrieval (CBIR) system, The solr is showing its port (8983), along with this, i have tried couple of IP addresses to access the solr server but failed. Kindly help me that how i can access the apache solr server? which ..
This code is intended to create an inverted index but when working with a wikipedia xml dump (~80GB) it runs out of memory. I haven’t been able to find out where the memory leak is happening and have explicitly deleted most of the data after using it. The xml dump is parsed using the sax ..
I have a dataset off millions of arrays like follows: sentences=[ [ ‘query_foo bar’, ‘split_query_foo’, ‘split_query_bar’, ‘sku_qwre’, ‘brand_A B C’, ‘split_brand_A’, ‘split_brand_B’, ‘split_brand_C’, ‘color_black’, ‘category_C1’, ‘product_group_clothing’, ‘silhouette_t_shirt_top’, ], […] ] where you find a query, a sku that was acquired by the user doing the query and a few attributes of the SKU. My idea ..
I would like to build a tool which searches the web for the most viewed and shared news articles published by the most popular news platforms (NYTimes, WSJ, etc.). I thought of scraping the internet sites for the articles and placing them in a data frame to later analyse them. I don’t know how to ..
I have a Django website and one of my models has an integer field. Does anyone know of a way to retrieve the largest value currently in that field into the view? Thanks! Source: Python..
So I was wondering after creating and inverted Index , how are they stored. I mean the format of the file , is going to be a csv file or txt file. Source: Python..
I have a vocabulary of unique words (excluding the stopwords) used over the entire document collection. I want to perform query expansion. In some approaches I have found that for every word in the query its top k synonyms (usually k=3) is augmented to the query. However, I am using a vector space model based ..