In my last post, I presented a code-dump that computed a restricted version of the tree edit distance algorithm. I was able to achieve a decent speed-up using enlive. Here’s a code-dump:
I had to throw together an implementation of tree-edit distance for clustering web-pages based on their structure. It performs reasonably quickly. The algorithm itself. The repo is here.
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(ns tree-edit-distance.core (:use [clojure.pprint]) (:import (org.htmlcleaner HtmlCleaner DomSerializer CleanerProperties) (org.w3c.dom Document))) (defn init "Perform the correct initialization" [m n c1 c2 del-cost ins-cost] (let [M (make-array Integer/TYPE (inc m) (inc n))] (do (doseq [i (range (inc m)) j (range (inc n))] (aset M i j (int (+ (* del-cost c1) (* ins-cost c2))))) M))) (defn num-children "Expects a html tree" [a-tree] (if(.hasChildNodes a-tree) (.getLength (.getChildNodes a-tree)) 0)) (defn tree-children "Return level 1 children" [a-tree] (let [n (num-children a-tree) cs (.getChildNodes a-tree)] (map #(.item cs %) (range n)))) (defn tree-descendants [a-tree] (if (.hasChildNodes a-tree) (concat (tree-children a-tree) (flatten (map tree-descendants (tree-children a-tree)))) )) (declare rtdm-edit-distance) (defn invert-cost [t1 t2 del-cost ins-cost sub-cost] (let [t1-desc (tree-descendants t1) t2-desc (tree-descendants t2)] (- (+ (* del-cost (count t1-desc)) (* ins-cost (count t2-desc))) (rtdm-edit-distance t1 t2 del-cost ins-cost sub-cost)))) (defn rtdm-edit-distance "The RTDM algorithm for computing edit-distance. The trees are assumed to be org.w3c.dom.Documents" [tree-1 tree-2 del-cost ins-cost sub-cost] (let [m (num-children tree-1) n (num-children tree-2) t1-children (tree-children tree-1) t2-children (tree-children tree-2) t1-desc (tree-descendants tree-1) t2-desc (tree-descendants tree-2) M (init m n (count t1-desc) (count t2-desc) del-cost ins-cost)] (doseq [i (range m) j (range n)] (let [c-i (nth t1-children i) c-j (nth t2-children j) c-i-desc (tree-descendants c-i) c-j-desc (tree-descendants c-j) del (aget M i (inc j)) ins (aget M (inc i) j) sub-i (- (aget M i j) del-cost ins-cost) sub (if (.isEqualNode c-i c-j) (- sub-i (* ins-cost (count c-j-desc)) (* del-cost (count c-i-desc))) (cond (or (not (.hasChildNodes c-i)) (not (.hasChildNodes c-j))) (+ sub-i sub-cost) (and (= (.getNodeName c-i) (.getNodeName c-j)) (try (= (.getNodeValue (.getNamedItem (.getAttributes c-i) "id")) (.getNodeValue (.getNamedItem (.getAttributes c-j) "id"))) (catch Exception e true)) (try (= (.getNodeValue (.getNamedItem (.getAttributes c-i) "class")) (.getNodeValue (.getNamedItem (.getAttributes c-j) "class"))) (catch Exception e true))) (- sub-i (invert-cost c-i c-j del-cost ins-cost sub-cost)) :else (+ sub-i sub-cost)))] (aset M (inc i) (inc j) (int (min del ins sub))))) (aget M m n))) (defn rtdm-edit-distance-sim [tree-1 tree-2 del-cost ins-cost sub-cost] (let [t1-desc (tree-descendants tree-1) t2-desc (tree-descendants tree-2)] (- 1 (/ (rtdm-edit-distance tree-1 tree-2 del-cost ins-cost sub-cost) (+ (* (+ (count t1-desc) 1) del-cost) (* (+ (count t2-desc) 1) sub-cost)))))) (defn get-xml-tree-body "Downloads a webpage and converts it to an org.w3.dom.Document" [page-src] (let [cleaner (new HtmlCleaner) props (.getProperties cleaner) cleaner-props (new CleanerProperties) dom-serializer (new DomSerializer cleaner-props) tag-node (.clean cleaner page-src)] (.createDOM dom-serializer tag-node))) (defn rtdm-edit-distance-html [pg1 pg2 del-cost ins-cost sub-cost] (rtdm-edit-distance-sim (get-xml-tree-body pg1) (get-xml-tree-body pg2) del-cost ins-cost sub-cost))
For my SIGIR submission I have been working on finding efficient traversal strategies while crawling websites.
Web crawling is a straightforward graph-traversal problem. My research focuses on discarding unproductive paths and preserving bandwidth to find more information. I will write a post on it once I have my ideas fleshed out and thus that won’t be the focus of this post.
Here, I will describe the finer details needed to make your crawler polite and robust. An impolite crawler will incur the wrath of an admin and might get you banned. A crawler that isn’t robust cannot survive the onslaught of quirks that the WWW is full of.
I recently gave a talk at CMU on the state of the Clueweb12++ crawl. Here are the slides.
The Clueweb12++ crawl aims at accumulating social media content from the Clueweb crawl’s time frame. Our pipeline thus far was as follows:
- Download a bunch of index pages from forums (index pages link to threads).
- Identify posts that fall in the time-frame specified.
- Download posts and recreate web-graph to give the impression of a crawl completed in the 2012 time-frame.
There is one complicated time-frame in this setup - step 2. Dates processing is a nuisance that I would not wish upon anyone else. There are an innumerable number of surface representations (that can be ambiguous) and to add to our troubles, people do stuff like use “Last Week” to indicate time of activity.
The most accurate tool is SUTime but on a crawl the size of ClueWeb, it is foolish to run such a crawl on it. So what we do is use Natty. Natty is fast and reasonably accurate.
I’ve uploaded a java module to github that will spit out a list of dates. You can obtain it here.
(c) Shriphani Palakodety 2013-2018