Lay the Mountains Low: The Flight of the Nez Perce from by Terry C. Johnston

By Terry C. Johnston

In the summertime of 1877, in a spot known as White poultry Canyon, Nez Perce warriors added a gorgeous blow to the 1st Cavalry—the worst defeat because the Little Bighorn twelve months ahead of. Now, common O.O. Howard is charged with weeding out the Nez Perce and defeating them eventually. keen to sacrifice their ancestral native land, with little knowing of the methods of the powerful U.S. govt, the Non-Treaty Nez Perce commence a push out of Idaho for Montana and for peace. however it is simply too past due. For warriors, infantrymen, and strategists—and the blameless stuck in between—a bloody battlefield awaits, at a spot referred to as immense gap, Montana...

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Read or Download Lay the Mountains Low: The Flight of the Nez Perce from Idaho and the Battle of the Big Hole, August 9-10, 1877 (The Plainsmen, Book 15) PDF

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Extra info for Lay the Mountains Low: The Flight of the Nez Perce from Idaho and the Battle of the Big Hole, August 9-10, 1877 (The Plainsmen, Book 15)

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The similarity between and is calculated using the cosine similarity function as follows: , ∑ ∑ ∑ Where and is the user’s preference to each attribute value for an active user and a previous user, respectively. One of the previous users who has the highest similarity value with the active user is selected as the active user’s neighbour, . 5 Products Recommendation When an active user’s neighbour has been identified, the session , ,… for this user is used to get products that have been viewed by this user to expand the active user’s query.

The possibility of being a long session for a session with a large length is greater than a session with a small length, and a set of cars with multiple different IDs can be considered more diverse than a set of cars with the same ID. In this part of evaluation, we want to investigate whether or not the length of the session influences the performance of the search models. The length of the session in runs R6 to R2 decreases, which means, the diversity of the cars from R6 to R2 decreases. R1 uses sessions of varying lengths.

The similarity between and is calculated using the cosine similarity function as follows: , ∑ ∑ ∑ Where and is the user’s preference to each attribute value for an active user and a previous user, respectively. One of the previous users who has the highest similarity value with the active user is selected as the active user’s neighbour, . 5 Products Recommendation When an active user’s neighbour has been identified, the session , ,… for this user is used to get products that have been viewed by this user to expand the active user’s query.

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